Traits In Sugarcane Research Articles

Identification and Functional Analysis of Strigolactone Pathway Genes Regulating Tillering Traits in Sugarcane.

Saccharum officinarum (S. officinarum) and Saccharum spontaneum (S. spontaneum) are two fundamental species of modern sugarcane cultivars, exhibiting divergent tillering patterns crucial for sugarcane architecture and yield. Strigolactones (SLs), a class of plant hormones, are considered to play a central role in shaping plant form and regulating tillering. Our study highlights the distinct tillering patterns observed between S. officinarum and S. spontaneum, and implicates significant differences in SL levels in root exudates between the two species. Treatment with rac-GR24 (an artificial strigolactone analog) suppressed tillering in S. spontaneum. Based on transcriptome analysis, we focused on two genes, TRANSCRIPTION ELONGATION FACTOR 1 (TEF1) and CIRCADIAN CLOCK ASSOCIATED1 (CCA1), which show higher expression in S. spontaneum or S. officinarum, respectively. While the overexpression of SoCCA1 did not lead to significant phenotypic differences, overexpression of SsTEF1 in rice stimulated tillering and inhibited plant height, demonstrating its role in tillering regulation. However, the overexpression of suggesting that SoCCA1 may not be the key regulator of sugarcane tillering. Yeast one-hybrid (Y1H) assays identified four transcription factors (TFs) regulating SsTEF1, four and five TFs regulating SsCCA1 and SoCCA1. This study provides a theoretical foundation for deciphering the molecular mechanisms underlying the different tillering behaviors between S. officinarum and S. spontaneum, providing valuable insights for the molecular-based design of sugarcane breeding strategies.

Multi-environment Analysis of Yield and Quality Traits in Sugarcane (Saccharum sp.) through AMMI and GGE Biplot Analysis

Multi-environment Analysis of Yield and Quality Traits in Sugarcane (Saccharum sp.) through AMMI and GGE Biplot Analysis

Dissection of genetic architecture for desirable traits in sugarcane by integrated transcriptomics and metabolomics

Sugarcane is an important sugar and energy crop. Breeding varieties with high yield and sugar, strong stress tolerance, as well as beneficial for mechanized harvesting are the goal of sugarcane breeder. In the present study, transcriptomics and metabolomics were conducted to explore the molecular basis for outstanding performance of five elite varieties GT42, GT44, LC05-136, YZ08-1609, and YZ05-51, along with the cross-parent CP72-1210 compared to ROC22. Transcriptomics revealed a total of 18,353 differentially expressed genes (DEGs) and several regulatory pathways, including carbon fixation, starch and sucrose metabolism, phenylpropanoids biosynthesis, flavonoid biosynthesis, cysteine and methionine metabolism, as well as zeatin biosynthesis. Expression patterns of genes involved in these pathways confirmed their role in determining the agronomic traits. Besides, metabolomics disclosed 175 differentially accumulated metabolites (DAMs), including specific metabolites of amino acids and secondary metabolites. Furthermore, conjoint analysis of transcriptomics and metabolomics highlighted the manipulation of 113 genes led to changed levels of 20 metabolites associated with carbon fixation, sucrose accumulation, phytohormone response and secondary metabolism. Finally, we depicted here a blueprint outlining the genetic basis underlying the desirable traits in sugarcane. This study will accelerate the dissection of the molecular basis for sugarcane traits and provide targets for molecular breeding.

Gas exchange and time to reach maximum rate of photosynthetic rate and their relationship with whole-plant traits in sugarcane in water abundant Louisiana, USA.

Variety development of sugarcane (Saccharum spp. hybrids) is necessary to continue improving sugar yields and selecting photosynthetic traits can improve sugar production through increased carbon inputs. In this study, gas exchange and whole-plant measurements were made on 55 sugarcane genotypes in Louisiana. Variation in the relationship between photosynthetic rate and stomatal conductance suggests that sugarcane exhibits variation in both photosynthetic capacity and CO2 substrate availability. Genotypes that reached maximum photosynthetic rate (TRMPR) in the gas-exchange cuvette more quickly had greater CO2 assimilation during transitory periods. Temporary shading and fluctuating light are common transitory conditions in the field, so increasing TRMPR can improve photosynthesis in water-abundant regions. Canopy leaf area was positively correlated with stalk mass, but gas-exchange traits were not correlated with whole-plant traits. A better understanding of the relationship between leaf and whole-plant traits is necessary to identify physiological traits that lead to increased genetic gain.

A SNP variation in the Sucrose synthase (SoSUS) gene associated with sugar-related traits in sugarcane.

Sugarcane (Saccharum spp.) is an economically significant crop for both the sugar and biofuel industries. Breeding sugarcane cultivars with high-performance agronomic traits is the most effective approach for meeting the rising demand for sugar and biofuels. Molecular markers associated with relevant agronomic traits could drastically reduce the time and resources required to develop new sugarcane varieties. Previous sugarcane candidate gene association analyses have found single nucleotide polymorphism (SNP) markers associated with sugar-related traits. This study aims to validate these associated SNP markers of six genes, including Lesion simulating disease 1 (LSD), Calreticulin (CALR), Sucrose synthase 1 (SUS1), DEAD-box ATP-dependent RNA helicase (RH), KANADI1 (KAN1), and Sodium/hydrogen exchanger 7 (NHX7), in a diverse population in 2-year and two-location evaluations. After genotyping of seven targeted SNP markers was performed by PCR Allelic Competitive Extension (PACE) SNP genotyping, the association with sugar-related traits and important cane yield component traits was determined on a set of 159 sugarcane genotypes. The marker-trait relationships were validated and identified by both t-test analysis and an association analysis based on the general linear model. The mSoSUS1_SNPCh10.T/C and mSoKAN1_SNPCh7.T/C markers that were designed from the SUS1 and KAN1 genes, respectively, showed significant associations with different amounts of sugar-related traits and yield components. The mSoSUS1_SNPCh10.T/C marker was found to have more significant association with sugar-related traits, including pol, CCS, brix, fiber and sugar yield, with p values of 6.08 × 10-6 to 4.35 × 10-2, as well as some cane yield component traits with p values of 1.61 × 10-4 to 3.35 × 10-2. The significant association is consistent across four environments. Sucrose synthase (SUS) is considered a crucial enzyme involved in sucrose metabolism. This marker is a high potential functional marker that may be used in sugarcane breeding programs to select superior sugarcane with good fiber and high sugar contents.

Validation of candidate gene-based EST-SSR markers for sugar yield in sugarcane.

Sugarcane (Saccharum spp.) is a widely cultivated crop that fulfils approximately 75% of the sucrose demand worldwide. Owing to its polyploidy and complex genetic nature, it is difficult to identify and map genes related to complex traits, such as sucrose content. However, association mapping is one of the alternatives for identifying genes or markers for marker-assisted selection. In the present study, EST-SSR primers were obtained from in silico studies. The functionality of each primer was tested using Blast2Go software, and 30 EST-SSR primers related to sugar content were selected. These markers were validated using association analysis. A total of 70 F1 diverse genotypes for sugar content were phenotypes with two check lines. All parameters related to sugar content were recorded. The results showed a significant variation between the genotypes for sugar yield traits such as Brix value, purity, and sucrose content, etc. Correlation studies revealed that the Brix%, sucrose content, and sucrose recovery were significantly correlated. An association analysis was performed using mixed linear model to avoid false positive associations. The association analysis revealed that the SEM 407 marker was significantly associated with Brix% and sucrose content. The SEM 407 primers are putatively related to diphosphate-fructose-6-phosphate 1-phosphotransferase which is associated with Brix% and sucrose content. This functional marker can be used for marker-assisted selection for sugar yield traits in sugarcane that could accelerate the sugarcane breeding program.

Genome-Wide Association Study Unravels Quantitative Trait Loci and Genes Associated with Yield-Related Traits in Sugarcane.

Sugarcane, a major sugar and energy crop worldwide faces an increasing demand for higher yields. Identifying yield-related markers and candidate genes is valuable for breeding high-yield varieties using molecular techniques. In this work, seven yield-related traits were evaluated in a diversity panel of 159 genotypes, derived from Tripidium arundinaceum, Saccharum spontaneum, and modern sugarcane genotypes. All traits exhibited significant genetic variance with high heritability and high correlations. Genetic diversity analysis reveals a genomic decay of 23 kb and an average single nucleotide polymorphism (SNP) number of 25,429 per genotype. These 159 genotypes were divided into 4 subgroups. Genome-wide association analysis identified 47 SNPs associated with brix, spanning 36 quantitative trait loci (QTLs), and 138 SNPs for other traits across 104 QTLs, covering all 32 chromosomes. Interestingly, 12 stable QTLs associated with yield-related traits were identified, which contained 35 candidate genes. This work provides markers and candidate genes for marker-assisted breeding to improve sugarcane yields.

A Large-Scale Candidate-Gene Association Mapping for Drought Tolerance and Agronomic Traits in Sugarcane.

Dissection of the genetic loci controlling drought tolerance traits with a complex genetic inheritance is important for drought-tolerant sugarcane improvement. In this study, we conducted a large-scale candidate gene association study of 649 candidate genes in a sugarcane diversity panel to identify genetic variants underlying agronomic traits and drought tolerance indices evaluated in plant cane and ratoon cane under water-stressed (WS) and non-stressed (NS) environments. We identified 197 significant marker-trait associations (MTAs) in 141 candidate genes associated with 18 evaluated traits with the Bonferroni correction threshold (α = 0.05). Out of the total, 95 MTAs in 78 candidate genes and 62 MTAs in 58 candidate genes were detected under NS and WS conditions, respectively. Most MTAs were found only in specific water regimes and crop seasons. These MTAs explained 7.93-30.52% of phenotypic variation. Association mapping results revealed that 34, 59, and 104 MTAs involved physiological and molecular adaptation, phytohormone metabolism, and drought-inducible genes. They identified 19 pleiotropic genes associated with more than one trait and many genes related to drought tolerance indices. The genetic and genomic resources identified in this study will enable the combining of yield-related traits and sugar-related traits with agronomic value to optimize the yield of sugarcane cultivars grown under drought-stressed and non-stressed environments.

Multiomic investigation of Sugarcane mosaic virus resistance in sugarcane

Sugarcane mosaic virus (SCMV) is the main etiological agent of sugarcane mosaic disease, which affects sugarcane and other grass crops. Despite the extensive characterization of quantitative trait loci controlling resistance to SCMV in maize, the genetic basis of this trait in sugarcane is largely unexplored. Here, a genome-wide association study was performed and machine learning coupled with feature selection was used for genomic prediction of resistance to SCMV in a diverse sugarcane panel. Nine single-nucleotide polymorphisms (SNPs) explained up to 29.9% of the observed phenotypic variance and a 73-SNP set predicted resistance with high accuracy, precision, recall, and F1 scores (the harmonic mean of precision and recall). Both marker sets were validated in additional sugarcane genotypes, in which the SNPs explained up to 23.6% of the phenotypic variation and predicted resistance with a maximum accuracy of 69.1%. Synteny analyses suggested that the gene responsible for the majority of SCMV resistance in maize is absent in sugarcane, explaining why this major resistance source has not been identified in this crop. Finally, using sugarcane RNA-Seq data, markers associated with resistance to SCMV were annotated, and a gene coexpression network was constructed to identify the predicted biological processes involved in resistance. This network allowed the identification of candidate resistance genes and confirmed the involvement of stress responses, photosynthesis, and the regulation of transcription and translation in resistance to SCMV. These results provide a practical marker-assisted breeding approach for sugarcane and identify target genes for future studies of SCMV resistance.

Combination of GWAS and FST-based approaches identified loci associated with economic traits in sugarcane.

Sugarcane is a globally important plant for both sugar and biofuel production. Although conventional breeding has played an important role in increasing the productivity of sugarcane, it takes a long time to achieve breeding goals such as high yield and resistant to diseases. Molecular breeding, including marker-assisted breeding and genomic selection, can accelerate genetic improvement by selecting elites at the seedling stage with DNA markers. However, only a few DNA markers associated with important traits were identified in sugarcane. The purpose of this study was to identify DNA markers associated with sugar content, stalk diameter, and sugarcane top borer resistance. The sugarcane samples with trait records were genotyped using the restriction site-associated DNA sequencing (RADseq) technology. Using FST analysis and genome-wide association study (GWAS), a total of 9, 23 and 9 DNA variants (single nucleotide polymorphisms (SNPs)/insertions and deletions (indels)) were associated with sugar content, stalk diameter, and sugarcane top borer resistance, respectively. The identified genetic variants were on different chromosomes, suggesting that these traits are complex and determined by multiple genetic factors. These DNA markers identified by both approaches have the potential to be used in selecting elite clones at the seeding stage in our sugarcane breeding program to accelerate genetic improvement. Certainly, it is essential to verify the reliability of the identified DNA markers associated with traits before they are used in molecular breeding in other populations.

Mapping of QTLs and Screening Candidate Genes Associated with the Ability of Sugarcane Tillering and Ratooning.

The processes of sugarcane tillering and ratooning, which directly affect the yield of plant cane and ratoon, are of vital importance to the population establishment and the effective stalk number per unit area. In the present study, the phenotypic data of 285 F1 progenies from a cross of sugarcane varieties YT93-159 × ROC22 were collected in eight environments, which consisted of plant cane and ratoon cultivated in three different ecological sites. The broad sense heritability (H2) of the tillering and the ratoon sprouting was 0.64 and 0.63, respectively, indicating that they were middle to middle-high heritable traits, and there is a significantly positive correlation between the two traits. Furthermore, a total of 26 quantitative trait loci (QTLs) related to the tillering ability and 11 QTLs associated with the ratooning ability were mapped on two high-quality genetic maps derived from a 100K SNP chip, and their phenotypic variance explained (PVE) ranged from 4.27-25.70% and 6.20-13.54%, respectively. Among them, four consistent QTLs of qPCTR-R9, qPCTR-Y28, qPCTR-Y60/qRSR-Y60 and PCTR-Y8-1/qRSR-Y8 were mapped in two environments, of which, qPCTR-Y8-1/qRSR-Y8 had the PVEs of 11.90% in the plant cane and 7.88% in the ratoon. Furthermore, a total of 25 candidate genes were identified in the interval of the above four consistent QTLs and four major QTLs of qPCTR-Y8-1, qPCTR-Y8-2, qRSR-R51 and qRSR-Y43-2, with the PVEs from 11.73-25.70%. All these genes were associated with tillering, including eight transcription factors (TFs), while 15 of them were associated with ratooning, of which there were five TFs. These QTLs and genes can provide a scientific reference for genetic improvement of tillering and ratooning traits in sugarcane.

Epigenetic and Genetic Contribution for Expression Bias of Homologous Alleles in Polyploid Sugarcane

DNA methylation regulates gene expression in eukaryotes, but their roles in gene expression changes in polyploids are poorly understood. Here, we comparatively analyzed the DNA methylation profiles and transcriptome maps of four tissues (leaf, rind, pith, and root) in autopolyploid sugarcane (Saccharum spontaneum). The overall DNA methylation levels were relatively equal and were consistent with the similar genome-wide expression levels of homologous alleles among different homologous chromosomes. However, tetrad alleles showed a large proportion of non-balanced alleles (85–89%) compared with balanced alleles (11–15%). For tetrad alleles, highly-expressed alleles showed lower Ka/Ks values than those in lowly-expressed alleles, indicating that dominant (and non-suppressed) alleles were under strong purifying selection pressure compared to non-dominant (and suppressed) alleles. Specifically, higher DNA methylation levels were found in non-balanced alleles compared to balanced alleles, as well as a higher CG to TG substitution rate, suggesting epigenetic and genetic variation associated with transcription divergence. Moreover, among non-balanced alleles, which were associated with DNA methylation changes, many were involved in several processes relevant to agronomic traits, such as responses to stress and carbohydrate transport. Taken together, our results provide unique epigenetic insights into the transcriptional regulation of homologous alleles, which contribute to the key agronomic traits in sugarcane and facilitate epigenetic studies in other polyploid crops.

Accuracy of Genomic Prediction of Yield and Sugar Traits in Saccharum spp. Hybrids

Genomic selection (GS) has been demonstrated to enhance the selection process in breeding programs. The objectives of this study were to experimentally evaluate different GS methods in sugarcane hybrids and to determine the prospect of GS in future breeding approaches. Using sugar and yield-related trait data from 432 sugarcane clones and 10,435 single nucleotide polymorphisms (SNPs), a study was conducted using seven different GS models. While fivefold cross-validated prediction accuracy differed by trait and by crop cycle, there were only small differences in prediction accuracy among the different models. Prediction accuracy was on average 0.20 across all traits and crop cycles for all tested models. Utilizing a trait-assisted GS model, we could effectively predict the fivefold cross-validated genomic estimated breeding value of ratoon crops using both SNPs and trait values from the plant cane crop. We found that the plateau of prediction accuracy could be achieved with 4000 to 5000 SNPs. Prediction accuracy did not decline with decreasing size of the training population until it was reduced below 60% (259) to 80% (346) of the original number of clones. Our findings suggest that GS is possibly a new direction for improving sugar and yield-related traits in sugarcane.

Prediction of morpho-physiological traits in sugarcane using aerial imagery and machine learning

Changes in morpho-physiological traits are important for biotic or abiotic stresses in sugarcane (Saccharum spp. interspecific hybrids). Ground measurements of such traits are labor-intensive and time-consuming. Therefore, predicting them using aerial imagery can be important for detecting stress and timely management. In this study, ground data and aerial imagery were collected from plant cane and first ratoon (two site-years) field trials of the last stage (Stage IV) of the Canal Point sugarcane cultivar development program in Florida. There were multiple genotypes (12 plant cane: 9 first ratoon) with six replications in each trial. Data were collected on soil plant analysis development (SPAD), leaf area index (LAI), plant height, normalized difference vegetation index (NDVI), and number of millable stalks per hectare. Aerial imageries were collected using a hyperspectral sensor, and ground data using handheld sensors and manual readings on multiple dates (April, July, and September) to determine the best timing in morpho-physiological trait prediction. The gradient boosting regression tree was selected as the best prediction model. The mean absolute percentage error (MAPE) was utilized to determine the model's prediction accuracy. Results showed that SPAD was predicted with higher accuracy (89%) compared to other traits. July was observed as the best time for predicting most of the morpho-physiological traits in plant cane and first ratoon. Furthermore, the NDVI values collected by GreenSeeker and UAV imaging were compared using the Bland-Altman degree of agreement, and it was found that the mean difference of NDVI values between the two sensing systems was low (0.09).

Genetic and phenotypic correlation and path coefficient analysis for traits in sugarcane

Genetic and phenotypic correlation and path coefficient analysis for traits in sugarcane

Comparative evaluation of growth, yield and yield attributing traits in sugarcane (Saccharum officinarum) under different soil moisture regimes

A field experiment was conducted during spring season of 2014–15 and 2015–16 at CCS HAU, RRS, Karnal to evaluate the response of four sugarcane (Saccharum officinarum L.) varieties differing in their maturity i.e. CoS 767 (Mid late), CoH128 (Mid late), CoJ 64 (Early) and Co 0238 (Early) to deficit irrigation. The experiment was conducted in split plot design with three replications. Based on available soil moisture (ASM), three treatments i.e. irrigation at 50% ASM (control), 40% ASM (mild stress) and 30% ASM (severe stress) were imposed in main plot and sugarcane varieties in sub-plot. Under deficit irrigation, leaf area, leaf area index (LAI), crop grown rate (CGR), relative growth rate (RGR) and net assimilation rate (NAR), significantly, reduced at 30–60 and 60–90 DAP in all the varieties and the varieties Co 0238 and CoS 767 showed least reduction. The yield parameters, viz. number of millable canes, cane length, internodal length and single cane weight reduced significantly under water limited conditions and proved to be the most sensitive yield components responsible for decrease in cane and sugar yield. Cane yield and sugar yield reduced by 36.18% and 40.47%, and 27.5% and 31.09% at 30% and 40% ASM level, respectively. Co 0238 produced highest average cane yield and sugar yield (83.05 and 10.17 t/ha) followed by CoS 767 (68.23 and 8.28 t/ ha). Moreover, after stress revival Co 0238 and CoS 767 were able to recover faster which qualified these varieties to face short periods of drought without major losses in the initial phase of development.

Genome-wide analysis of R2R3-MYB transcription factors family in the autopolyploid Saccharum spontaneum: an exploration of dominance expression and stress response

BackgroundSugarcane (Saccharum) is the most critical sugar crop worldwide. As one of the most enriched transcription factor families in plants, MYB genes display a great potential to contribute to sugarcane improvement by trait modification. We have identified the sugarcane MYB gene family at a whole-genome level through systematic evolution analyses and expression profiling. R2R3-MYB is a large subfamily involved in many plant-specific processes.ResultsA total of 202 R2R3-MYB genes (356 alleles) were identified in the polyploid Saccharum spontaneum genomic sequence and classified into 15 subgroups by phylogenetic analysis. The sugarcane MYB family had more members by a comparative analysis in sorghum and significant advantages among most plants, especially grasses. Collinearity analysis revealed that 70% of the SsR2R3-MYB genes had experienced duplication events, logically suggesting the contributors to the MYB gene family expansion. Functional characterization was performed to identify 56 SsR2R3-MYB genes involved in various plant bioprocesses with expression profiling analysis on 60 RNA-seq databases. We identified 22 MYB genes specifically expressed in the stem, of which RT-qPCR validated MYB43, MYB53, MYB65, MYB78, and MYB99. Allelic expression dominance analysis implied the differential expression of alleles might be responsible for the high expression of MYB in the stem. MYB169, MYB181, MYB192 were identified as candidate C4 photosynthetic regulators by C4 expression pattern and robust circadian oscillations. Furthermore, stress expression analysis showed that MYB36, MYB48, MYB54, MYB61 actively responded to drought treatment; 19 and 10 MYB genes were involved in response to the sugarcane pokkah boeng and mosaic disease, respectively.ConclusionsThis is the first report on genome-wide analysis of the MYB gene family in sugarcane. SsMYBs probably played an essential role in stem development and the adaptation of various stress conditions. The results will provide detailed insights and rich resources to understand the functional diversity of MYB transcription factors and facilitate the breeding of essential traits in sugarcane.

Estimating Best Linear Unbiased Predictions (BLUP) for Yield and Quality Traits in Sugarcane

Estimating Best Linear Unbiased Predictions (BLUP) for Yield and Quality Traits in Sugarcane

English

Sugarcane smut caused by Sporisorium scitanmineumis the most severe sugarcane disease that causes major economic losses in sugarcane production in China, and disease resistance breeding is an important way of preventing and controlling this disease. In this study, BC3F1lines derived from the cross between YC 73-226 and YCE 06-111 were used to generate sugarcane smut-resistant and -susceptible gene pools using bulked segregant analysis (BSA). Eighty-nine random primers of start codon targeted (SCoT) polymorphisms were screened, whereas only primer SCoT44 could stably amplify the specific fragment (HE-Ss44) in the resistant pool. Then, several primer pairs of sequence characterized amplified regions (SCARs) were designed based on the sequence alignment of HE-Ss44 (920 bp), which was recovered after purification, and only one pair of SCAR primers (Ss44-F2/R2, forward: 5'-GGCGGGCACCGTCGAGTCCACAT-3'; reverse: 5'-CCGTCCGTCGG TCTCGTCCTTACG-3') could stably amplify a 400-bp specific band in resistant gene pool and its individuals. A validation test of SCAR marker Ss44-F2/R2 was performed using 34 sugarcane cultivars with known smut resistance, which revealed a selection accuracy of 82.35% between marker detection and known smut resistance. Moreover, Pearson’s correlation analysis also showed that the SCAR marker Ss44-F2/R2 was significantly correlated (r= 0.583, P= 0.0003 < 0.01) with the smut resistance trait in sugarcane. In addition, the nucleotide sequence of HE-Ss44 linked with smut-resistancewas not aligned to the homologous sequence in GenBank (NCBI), and the accession number was MG740763. The SCAR marker Ss44-F2/R2 developed in this study can be used for the rapid detection of smut resistance in sugarcane and may be utilized as reference for the improvement of sugarcane smut resistance based on molecular marker-assisted selection.© 2021 Friends Science Publishers

Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects

Key messageNon-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance.In the recent decade, genetic progress has been slow in sugarcane. One reason might be that non-additive genetic effects contribute substantially to complex traits. Dense marker information provides the opportunity to exploit non-additive effects in genomic prediction. In this study, a series of genomic best linear unbiased prediction (GBLUP) models that account for additive and non-additive effects were assessed to improve the accuracy of clonal prediction. The reproducible kernel Hilbert space model, which captures non-additive genetic effects, was also tested. The models were compared using 3,006 genotyped elite clones measured for cane per hectare (TCH), commercial cane sugar (CCS), and Fibre content. Three forward prediction scenarios were considered to investigate the robustness of genomic prediction. By using a pseudo-diploid parameterization, we found significant non-additive effects that accounted for almost two-thirds of the total genetic variance for TCH. Average heterozygosity also had a major impact on TCH, indicating that directional dominance may be an important source of phenotypic variation for this trait. The extended-GBLUP model improved the prediction accuracies by at least 17% for TCH, but no improvement was observed for CCS and Fibre. Our results imply that non-additive genetic variance is important for complex traits in sugarcane, although further work is required to better understand the variance component partitioning in a highly polyploid context. Genomics-based breeding will likely benefit from exploiting non-additive genetic effects, especially in designing crossing schemes. These findings can help to improve clonal prediction, enabling a more accurate identification of variety candidates for the sugarcane industry.