Machine learning for genomic and pedigree prediction in sugarcane.

Sugarcane (Saccharum spp.) plays a crucial role in global sugar production; however, the efficiency of breeding programs has been hindered by its heterozygous polyploid genomes. Considering non-additive genetic effects is essential in genome prediction (GP) models of crops with highly heterozygous polyploid genomes. This study incorporates non-additive genetic effects and pedigree information using machine learning methods to track sugarcane breeding lines and enhance the prediction by assessing the degree of association between genotypes. This study measured the stalk biomass and sugar content of 297 clones from 87 families within a breeding population used in the Japanese sugarcane breeding program. Subsequently, we conducted analyses based on the marker genotypes of 33,149 single-nucleotide polymorphisms. To validate the accuracy of GP in the population, we first predicted the prediction accuracy of the best linear unbiased prediction (BLUP) based on a genomic relationship matrix. Prediction accuracy was assessed using two different cross-validation methods: repeated 10-fold cross-validation and leave-one-family-out cross-validation. The accuracy of GP of the first and second methods ranged from 0.36 to 0.74 and 0.15 to 0.63, respectively. Next, we compared the prediction accuracy of BLUP and two machine learning methods: random forests and simulation annealing ensemble (SAE), a newly developed machine learning method that explicitly models the interaction between variables. Both pedigree and genomic information were utilized as input in these methods. Through repeated 10-fold cross-validation, we found that the accuracy of the machine learning methods consistently surpassed that of BLUP in most cases. In leave-one-family-out cross-validation, SAE demonstrated the highest accuracy among the methods. These results underscore the effectiveness of GP in Japanese sugarcane breeding and highlight the significant potential of machine learning methods.

Detection of a major QTL related to smut disease resistance inherited from a Japanese wild sugarcane using GRAS-Di technology.

Smut disease of sugarcane causes considerable yield losses and the use of resistant varieties is the best control practice. Our group identified a Japanese wild sugarcane with highly smut disease resistance named 'Iriomote8'. In this study, we conducted QTL analysis for smut disease resistance using a mapping population derived from a resistant variety 'Yaenoushie', in which resistance is inherited from 'Iriomote8'. We identified 4813 non-redundant markers using GRAS-Di technology and developed a linkage map of mapping parents. We evaluated smut disease resistance of the mapping population by the inoculation test. Consequently, a large number of clones did not show the disease symptoms and the distribution of smut disease incidence tended to be "L shaped". Composite interval mapping detected an identical QTL for indices of smut disease incidence with a markedly high LOD score (26.6~45.6) at the end of linkage group 8 of 'Yaenoushie'. This QTL explained approximately 50% of the cases of smut disease incidence. In the mapping population, there were no correlations between the indices of smut disease incidence and other agronomic traits. In conclusion, this QTL could be used for marker-assisted selection to significantly improve smut disease resistance without negative effects on other agronomic traits.

Silicon-induced changes in viscoelastic properties of sorghum root cell walls.

Silicon is deposited in the endodermal tissue in sorghum (Sorghum bicolor L. Moench) roots. Its deposition is thought to protect vascular tissues in the stele against invasion by parasites and drying soil via hardening of endodermal cells. We studied the silicon-induced changes in mechanical properties of cell walls to clarify the role of silicon in sorghum root. Sorghum seedlings were grown in nutrient solution with or without silicon. The mechanical properties of cell walls were measured in three separated root zones: basal, apical and subapical. Silicon treatment decreased cell-wall extensibility in the basal zone of isolated stele tissues covered by endodermal inner tangential walls. The silicon-induced hardening of cell walls was also measured with increases in elastic moduli (E) and viscosity coefficients (eta). These results provided new evidence that silicon deposition might protect the stele as a mechanical barrier by hardening the cell walls of stele and endodermal tissues. In contrast to the basal zone, silicon treatment increased cell-wall extensibility in the apical and subapical zones with concomitant decrease in E and eta. Simultaneously, silicon promoted root elongation. When root elongation is promoted by silicon, one of the causal factors maybe the silicon-enhanced extensibility of cell walls in the growing zone.

The dynamics of silicon deposition in the sorghum root endodermis.

• The dynamics of silica deposition and Si aggregates formation in inner tangential walls of root endodermal cells, which occurs as an additional stage of endodermal development in sorghum (Sorghum bicolor), were studied. • An environmental scanning electron microscope (ESEM) and X-ray microanalyzer (EDAX) were used to study sorghum roots grown hydroponically with Si (+ Si medium) and without Si (- Si medium). • Silica aggregates were absent in roots of plants cultivated in - Si medium. However, their additional formation on fully mature and thickened endodermal cell walls took place when plants grown in - Si medium were transferred to + Si medium. The beginning of Si aggregates formation was observed and Si deposition detected 2 h after transfer to + Si medium. • By dipping the apical root half in + Si medium, the silica aggregates were formed in the endodermis at the basal part of the root. This supports the hypothesis of outward Si transport from the xylem to the endodermis rather than radial inward Si movement and its deposition at the point of the apoplastic barrier represented by the endodermis.

Silicification in sorghum (Sorghum bicolor) cultivars with different drought tolerance.

Sorghum belongs to a group of economically important, silicon accumulating plants. X-ray microanalysis coupled with environmental scanning electron microscopy (ESEM) of fresh root endodermal and leaf epidermal samples confirms histological and cultivar specificity of silicification. In sorghum roots, silicon is accumulated mostly in endodermal cells. Specialized silica aggregates are formed predominantly in a single row in the form of wall outgrowths on the inner tangential endodermal walls. The density of silica aggregates per square mm of inner tangential endodermal cell wall is around 2700 and there is no significant difference in the cultivars with different content of silicon in roots. In the leaf epidermis, silicon deposits were present in the outer walls of all cells, with the highest concentration in specialized idioblasts termed 'silica cells'. These cells are dumb-bell shaped in sorghum. In both the root endodermis and leaf epidermis, silicification was higher in a drought tolerant cultivar Gadambalia compared with drought sensitive cultivar Tabat. Silicon content per dry mass was higher in leaves than in roots in both cultivars. The values for cv. Gadambalia in roots and leaves are 3.5 and 4.1% Si, respectively, and for cv. Tabat 2.2 and 3.3%. However, based on X-ray microanalysis the amount of Si deposited in endodermal cell walls in drought tolerant cultivar (unlike the drought susceptible cultivar) is higher than that deposited in the leaf epidermis. The high root endodermal silicification might be related to a higher drought resistance.