Yellow Leaf Disease Resistance and Melanaphis sacchari Preference in Commercial Sugarcane Cultivars.

Sugarcane yellow leaf disease (YLD) caused by sugarcane yellow leaf virus (ScYLV) is a major threat for the sugarcane industry worldwide, and the aphid Melanaphis sacchari is its main vector. Breeding programs in Brazil have provided cultivars with intermediate resistance to ScYLV, whereas the incidence of ScYLV has been underestimated partly due to the complexity of YLD symptom expression and identification. Here, we evaluated YLD symptoms in a field assay using eight sugarcane genotypes comprising six well-established commercial high-sucrose cultivars, one biomass yield cultivar, and a susceptible reference under greenhouse conditions, along with estimation of virus titer through RT-qPCR from leaf samples. Additionally, a free-choice bioassay was used to determine the number of aphids feeding on the SCYLV-infected cultivars. Most of the cultivars showed some degree of resistance to YLD, while also revealing positive RT-qPCR results for ScYLV and virus titers with non-significant correlation with YLD severity. The cultivars IACSP01-5503 and IACBIO-266 were similar in terms of aphid preference and ScYLV resistance traits, whereas the least preferred cultivar by M. sacchari, IACSP96-7569, showed intermediate symptoms but similar virus titer to the susceptible reference, SP71-6163. We conclude that current genetic resistance incorporated into sugarcane commercial cultivars does not effectively prevent the spread of ScYLV by its main aphid vector.

Taxonomically Restricted Genes Are Associated With Responses to Biotic and Abiotic Stresses in Sugarcane (Saccharum spp.).

Orphan genes (OGs) are protein-coding genes that are restricted to particular clades or species and lack homology with genes from other organisms, making their biological functions difficult to predict. OGs can rapidly originate and become functional; consequently, they may support rapid adaptation to environmental changes. Extensive spread of mobile elements and whole-genome duplication occurred in the Saccharum group, which may have contributed to the origin and diversification of OGs in the sugarcane genome. Here, we identified and characterized OGs in sugarcane, examined their expression profiles across tissues and genotypes, and investigated their regulation under varying conditions. We identified 319 OGs in the Saccharum spontaneum genome without detected homology to protein-coding genes in green plants, except those belonging to Saccharinae. Transcriptomic analysis revealed 288 sugarcane OGs with detectable expression levels in at least one tissue or genotype. We observed similar expression patterns of OGs in sugarcane genotypes originating from the closest geographical locations. We also observed tissue-specific expression of some OGs, possibly indicating a complex regulatory process for maintaining diverse functional activity of these genes across sugarcane tissues and genotypes. Sixty-six OGs were differentially expressed under stress conditions, especially cold and osmotic stresses. Gene co-expression network and functional enrichment analyses suggested that sugarcane OGs are involved in several biological mechanisms, including stimulus response and defence mechanisms. These findings provide a valuable genomic resource for sugarcane researchers, especially those interested in selecting stress-responsive genes.

A joint learning approach for genomic prediction in polyploid grasses.

Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in different cross-validation scenarios. By combining classification and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains.

Transcriptomic Analysis of Changes in Gene Expression During Flowering Induction in Sugarcane Under Controlled Photoperiodic Conditions.

Flowering is of utmost relevance for the agricultural productivity of the sugarcane bioeconomy, but data and knowledge of the genetic mechanisms underlying its photoperiodic induction are still scarce. An understanding of the molecular mechanisms that regulate the transition from vegetative to reproductive growth in sugarcane could provide better control of flowering for breeding. This study aimed to investigate the transcriptome of +1 mature leaves of a sugarcane cultivar subjected to florally inductive and non-inductive photoperiodic treatments to identify gene expression patterns and molecular regulatory modules. We identified 7,083 differentially expressed (DE) genes, of which 5,623 showed significant identity to other plant genes. Functional group analysis showed differential regulation of important metabolic pathways involved in plant development, such as plant hormones (i.e., cytokinin, gibberellin, and abscisic acid), light reactions, and photorespiration. Gene ontology enrichment analysis revealed evidence of upregulated processes and functions related to the response to abiotic stress, photoprotection, photosynthesis, light harvesting, and pigment biosynthesis, whereas important categories related to growth and vegetative development of plants, such as plant organ morphogenesis, shoot system development, macromolecule metabolic process, and lignin biosynthesis, were downregulated. Also, out of 76 sugarcane transcripts considered putative orthologs to flowering genes from other plants (such as Arabidopsis thaliana, Oryza sativa, and Sorghum bicolor), 21 transcripts were DE. Nine DE genes related to flowering and response to photoperiod were analyzed either at mature or spindle leaves at two development stages corresponding to the early stage of induction and inflorescence primordia formation. Finally, we report a set of flowering-induced long non-coding RNAs and describe their level of conservation to other crops, many of which showed expression patterns correlated against those in the functionally grouped gene network.

Genome-wide approaches for the identification of markers and genes associated with sugarcane yellow leaf virus resistance.

Sugarcane yellow leaf (SCYL), caused by the sugarcane yellow leaf virus (SCYLV) is a major disease affecting sugarcane, a leading sugar and energy crop. Despite damages caused by SCYLV, the genetic base of resistance to this virus remains largely unknown. Several methodologies have arisen to identify molecular markers associated with SCYLV resistance, which are crucial for marker-assisted selection and understanding response mechanisms to this virus. We investigated the genetic base of SCYLV resistance using dominant and codominant markers and genotypes of interest for sugarcane breeding. A sugarcane panel inoculated with SCYLV was analyzed for SCYL symptoms, and viral titer was estimated by RT-qPCR. This panel was genotyped with 662 dominant markers and 70,888 SNPs and indels with allele proportion information. We used polyploid-adapted genome-wide association analyses and machine-learning algorithms coupled with feature selection methods to establish marker-trait associations. While each approach identified unique marker sets associated with phenotypes, convergences were observed between them and demonstrated their complementarity. Lastly, we annotated these markers, identifying genes encoding emblematic participants in virus resistance mechanisms and previously unreported candidates involved in viral responses. Our approach could accelerate sugarcane breeding targeting SCYLV resistance and facilitate studies on biological processes leading to this trait.

The Wild Sugarcane and Sorghum Kinomes: Insights Into Expansion, Diversification, and Expression Patterns.

The protein kinase (PK) superfamily is one of the largest superfamilies in plants and the core regulator of cellular signaling. Despite this substantial importance, the kinomes of sugarcane and sorghum have not been profiled. Here, we identified and profiled the complete kinomes of the polyploid Saccharum spontaneum (Ssp) and Sorghum bicolor (Sbi), a close diploid relative. The Sbi kinome was composed of 1,210 PKs; for Ssp, we identified 2,919 PKs when disregarding duplications and allelic copies, and these were related to 1,345 representative gene models. The Ssp and Sbi PKs were grouped into 20 groups and 120 subfamilies and exhibited high compositional similarities and evolutionary divergences. By utilizing the collinearity between the species, this study offers insights into Sbi and Ssp speciation, PK differentiation and selection. We assessed the PK subfamily expression profiles via RNA-Seq and identified significant similarities between Sbi and Ssp. Moreover, coexpression networks allowed inference of a core structure of kinase interactions with specific key elements. This study provides the first categorization of the allelic specificity of a kinome and offers a wide reservoir of molecular and genetic information, thereby enhancing the understanding of Sbi and Ssp PK evolutionary history.

Epigenetic diversity of Saccharum spp. accessions assessed by methylation-sensitive amplification polymorphism (MSAP).

The epigenetic diversity of six genotype groups (commercial cultivars, S. officinarum, S. spontaneum, S. robustum, S. barberi, and Erianthus sp.) was assessed through methylation-sensitive amplification polymorphism (MSAP). A total of 1341 MSAP loci were analyzed, of which 1117 (83.29%) were susceptible to cytosine methylation and responsible for a higher proportion of overall diversity among genotypes. The MSAP selective primer combinations captured different proportions of internal and external cytosine methylation loci across genotype groups, while the average external cytosine frequency was higher for all genotype groups. The genotypes were divided into two subpopulations with a high differentiation index (φst = 0.086) based on epigenetic loci. The genotypes were clustered in three subgroups for both methylated and unmethylated loci, considering dissimilarity values. Four methylated fragments (MFs) were randomly selected and subsequently sequenced and compared with sugarcane public databases using BLASTN. MF alignments suggest that cytosine methylation occurs in sugarcane near CpG islands and tandem repeats within transcribed regions and putative cis-regulatory sequences, which assigned functions are associated with stress adaptation. These results provide the first insights about the distribution of this epigenetic mark in sugarcane genome, and suggest a biological relevance of methylated loci.

Sugarcane mosaic virus mediated changes in cytosine methylation pattern and differentially transcribed fragments in resistance-contrasting sugarcane genotypes.

Sugarcane mosaic virus (SCMV) is the causal agent of sugarcane mosaic disease (SMD) in Brazil; it is mainly controlled by using resistant cultivars. Studies on the changes in sugarcane transcriptome provided the first insights about the molecular basis underlying the genetic resistance to SMD; nonetheless, epigenetic modifications such as cytosine methylation is also informative, considering its roles in gene expression regulation. In our previous study, differentially transcribed fragments (DTFs) were obtained using cDNA-amplified fragment length polymorphism by comparing mock- and SCMV-inoculated plants from two sugarcane cultivars with contrasting responses to SMD. In this study, the identification of unexplored DTFs was continued while the same leaf samples were used to evaluate SCMV-mediated changes in the cytosine methylation pattern by using methylation-sensitive amplification polymorphism. This analysis revealed minor changes in cytosine methylation in response to SCMV infection, but distinct changes between the cultivars with contrasting responses to SMD, with higher hypomethylation events 24 and 72 h post-inoculation in the resistant cultivar. The differentially methylated fragments (DMFs) aligned with transcripts, putative promoters, and genomic regions, with a preponderant distribution within CpG islands. The transcripts found were associated with plant immunity and other stress responses, epigenetic changes, and transposable elements. The DTFs aligned with transcripts assigned to stress responses, epigenetic changes, photosynthesis, lipid transport, and oxidoreductases, in which the transcriptional start site is located in proximity with CpG islands and tandem repeats. Real-time quantitative polymerase chain reaction results revealed significant upregulation in the resistant cultivar of aspartyl protease and VQ protein, respectively, selected from DMF and DTF alignments, suggesting their roles in genetic resistance to SMD and supporting the influence of cytosine methylation in gene expression. Thus, we identified new candidate genes for further validation and showed that the changes in cytosine methylation may regulate important mechanisms underlying the genetic resistance to SMD.

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance.

Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust resistance is a desirable characteristic due to the large economic impact of the disease. Although marker-assisted selection for rust resistance has been successful, the genes involved are still unknown, and the associated regions vary among cultivars, thus restricting methodological generalization. We used genotyping by sequencing of full-sib progeny to relate genomic regions with brown rust phenotypes. We established a pipeline to identify reliable SNPs in complex polyploid data, which were used for phenotypic prediction via machine learning. We identified 14,540 SNPs, which led to a mean prediction accuracy of 50% when using different models. We also tested feature selection algorithms to increase predictive accuracy, resulting in a reduced dataset with more explanatory power for rust phenotypes. As a result of this approach, we achieved an accuracy of up to 95% with a dataset of 131 SNPs related to brown rust QTL regions and auxiliary genes. Therefore, our novel strategy has the potential to assist studies of the genomic organization of brown rust resistance in sugarcane.

Reference genes for gene expression studies targeting sugarcane infected with Sugarcane mosaic virus (SCMV).

OBJECTIVE: The selection of reference genes in sugarcane under Sugarcane mosaic virus (SCMV) infection has not been reported and is indispensable to get reliable reverse transcription quantitative PCR (RT-qPCR) results for validation of transcriptome analysis. In this regard, seven potential reference genes were tested by RT-qPCR and ranked according to their stability using BestKeeper, NormFinder and GeNorm algorithms, and RefFinder WEB-based software in an experiment performed with samples from two sugarcane cultivars contrasting for SCMV resistance, when mechanically inoculated with a severe SCMV strain and using mock inoculated plant controls. RESULTS: The genes Uridylate kinase (UK) and Ubiquitin-conjugating enzyme 18 (UBC18) were the most stable according to GeNorm algorithm and the Pearson correlation coefficients with the BestKeeper index. On the other hand, ribosomal protein L35-4 (RPL1), Actin (ACT) and Ubiquitin1 (UBQ1) were the least stable genes for all algorithms tested.

Gene Duplication in the Sugarcane Genome: A Case Study of Allele Interactions and Evolutionary Patterns in Two Genic Regions.

Sugarcane (Saccharum spp.) is highly polyploid and aneuploid. Modern cultivars are derived from hybridization between S. officinarum and S. spontaneum. This combination results in a genome exhibiting variable ploidy among different loci, a huge genome size (~10 Gb) and a high content of repetitive regions. An approach using genomic, transcriptomic, and genetic mapping can improve our knowledge of the behavior of genetics in sugarcane. The hypothetical HP600 and Centromere Protein C (CENP-C) genes from sugarcane were used to elucidate the allelic expression and genomic and genetic behaviors of this complex polyploid. The physically linked side-by-side genes HP600 and CENP-C were found in two different homeologous chromosome groups with ploidies of eight and ten. The first region (Region01) was a Sorghum bicolor ortholog region with all haplotypes of HP600 and CENP-C expressed, but HP600 exhibited an unbalanced haplotype expression. The second region (Region02) was a scrambled sugarcane sequence formed from different noncollinear genes containing partial duplications of HP600 and CENP-C (paralogs). This duplication resulted in a non-expressed HP600 pseudogene and a recombined fusion version of CENP-C and the orthologous gene Sobic.003G299500 with at least two chimeric gene haplotypes expressed. It was also determined that it occurred before Saccharum genus formation and after the separation of sorghum and sugarcane. A linkage map was constructed using markers from nonduplicated Region01 and for the duplication (Region01 and Region02). We compare the physical and linkage maps, demonstrating the possibility of mapping markers located in duplicated regions with markers in nonduplicated region. Our results contribute directly to the improvement of linkage mapping in complex polyploids and improve the integration of physical and genetic data for sugarcane breeding programs. Thus, we describe the complexity involved in sugarcane genetics and genomics and allelic dynamics, which can be useful for understanding complex polyploid genomes.

Unraveling the genetic structure of Brazilian commercial sugarcane cultivars through microsatellite markers.

The Brazilian sugarcane industry plays an important role in the worldwide supply of sugar and ethanol. Investigation into the genetic structure of current commercial cultivars and comparisons to the main ancestor species allow sugarcane breeding programs to better manage crosses and germplasm banks as well as to promote its rational use. In the present study, the genetic structure of a group of Brazilian cultivars currently grown by commercial producers was assessed through microsatellite markers and contrasted with a group of basic germplasm mainly composed of Saccharum officinarum and S. spontaneum accessions. A total of 285 alleles was obtained by a set of 12 SSRs primer pairs that taken together were able to efficiently distinguish and capture the genetic variability of sugarcane commercial cultivars and basic germplasm accessions allowing its application in a fast and cost-effective way for routine cultivar identification and management of sugarcane germplasm banks. Allelic distribution revealed that 97.6% of the cultivar alleles were found in the basic germplasm while 42% of the basic germplasm alleles were absent in cultivars. Of the absent alleles, 3% was exclusive to S. officinarum, 33% to S. spontaneum and 19% to other species/exotic hybrids. We found strong genetic differentiation between the Brazilian commercial cultivars and the two main species (S. officinarum: [Formula: see text] = 0.211 and S. spontaneum: [Formula: see text] = 0.216, P<0.001), and significant contribution of the latter in the genetic variability of commercial cultivars. Average dissimilarity within cultivars was 1.2 and 1.4 times lower than that within S. officinarum and S. spontaneum. Genetic divergence found between cultivars and S. spontaneum accessions has practical applications for energy cane breeding programs as the choice of more divergent parents will maximize the frequency of transgressive individuals in the progeny.

De novo assembly and transcriptome analysis of contrasting sugarcane varieties.

Sugarcane is an important crop and a major source of sugar and alcohol. In this study, we performed de novo assembly and transcriptome annotation for six sugarcane genotypes involved in bi-parental crosses. The de novo assembly of the sugarcane transcriptome was performed using short reads generated using the Illumina RNA-Seq platform. We produced more than 400 million reads, which were assembled into 72,269 unigenes. Based on a similarity search, the unigenes showed significant similarity to more than 28,788 sorghum proteins, including a set of 5,272 unigenes that are not present in the public sugarcane EST databases; many of these unigenes are likely putative undescribed sugarcane genes. From this collection of unigenes, a large number of molecular markers were identified, including 5,106 simple sequence repeats (SSRs) and 708,125 single-nucleotide polymorphisms (SNPs). This new dataset will be a useful resource for future genetic and genomic studies in this species.

Survey in the sugarcane expressed sequence tag database (SUCEST) for simple sequence repeats.

Sugarcane microsatellites or simple sequence repeats (SSR) were developed in an economical and practical way by mining EST databases. A survey in the SUCEST (sugarcane EST) database revealed a total of 2005 clusters out of 43,141 containing SSRs. Of these, 8.2% were dinucleotide, 30.5% were trinucleotide, and 61.3% were tetranucleotide repeats. Except for dinucleotides, the CG-rich motif types were the most common. Differences in abundance of trinucleotide motif types were observed between EST-SSRs and those isolated from sugarcane genomic libraries. Among the different cDNA libraries used for EST sequencing, SSRs were more frequent in the ones derived from leaf roll (LR). Twenty-three out of 30 tested SSRs produced scorable polymorphisms in 18 sugarcane commercial clones. These EST-SSRs showed a moderate level of polymorphism with some SSRs producing unique fingerprints. The number of alleles observed among the 18 clones evaluated varied from 2 to 15, with an average of 6.04 alleles/locus. The polymorphism information content (PIC) values ranged from 0.28 to 0.90 with a mean of 0.66. The EST-SSRs screened over both parents (SP 80-180; SP 80-4966) and 6 F1 individuals produced 52 segregating markers that could potentially be used for sugarcane mapping. The EST-SSRs were found in clusters that had significant homology to proteins involved in important metabolic pathways such as sugar biosynthesis, proving that EST-SSRs are a valuable tool for the construction of a functional sugarcane map.

Reciprocal recurrent selection effects on the genetic structure of tropical maize populations assessed at microsatellite loci

A modified reciprocal recurrent selection (RRS) method, which employed one cycle of high-intensity selection, was applied to two tropical maize (Zea mays L.) populations, BR-105 and BR-106, originating the improved synthetics IG-3 and IG-4, respectively. In the present study the effects of this kind of selection on the genetic structure of these populations and their synthetics were investigated at 30 microsatellite (SSR) loci. A total of 125 alleles were revealed. A reduction in the number of alleles was observed after selection, as well as changes in allele frequencies. In nearly 13 percent (BR-105) and 7 percent (BR-106) of the loci evaluated, the changes in allele frequencies were not explained, exclusively due to the effects of genetic drift. The effective population sizes estimated for the synthetics using 30 SSR loci were similar to those theoretically expected after selection. The genetic differentiation (G ST) between the synthetics increased to 77 percent compared with the original populations. The estimated R ST values, a genetic differentiation measure proper for microsatellite data, were similar to those obtained for G ST. Despite the high level of selection applied, the total gene diversity found in the synthetics allows them to be used in a new RRS cycle