GBS-based single dosage markers for linkage and QTL mapping allow gene mining for yield-related traits in sugarcane.

BACKGROUND: Sugarcane (Saccharum spp.) is predominantly an autopolyploid plant with a variable ploidy level, frequent aneuploidy and a large genome that hampers investigation of its organization. Genetic architecture studies are important for identifying genomic regions associated with traits of interest. However, due to the genetic complexity of sugarcane, the practical applications of genomic tools have been notably delayed in this crop, in contrast to other crops that have already advanced to marker-assisted selection (MAS) and genomic selection. High-throughput next-generation sequencing (NGS) technologies have opened new opportunities for discovering molecular markers, especially single nucleotide polymorphisms (SNPs) and insertion-deletion (indels), at the genome-wide level. The objectives of this study were to (i) establish a pipeline for identifying variants from genotyping-by-sequencing (GBS) data in sugarcane, (ii) construct an integrated genetic map with GBS-based markers plus target region amplification polymorphisms and microsatellites, (iii) detect QTLs related to yield component traits, and (iv) perform annotation of the sequences that originated the associated markers with mapped QTLs to search putative candidate genes. RESULTS: We used four pseudo-references to align the GBS reads. Depending on the reference, from 3,433 to 15,906 high-quality markers were discovered, and half of them segregated as single-dose markers (SDMs) on average. In addition to 7,049 non-redundant SDMs from GBS, 629 gel-based markers were used in a subsequent linkage analysis. Of 7,678 SDMs, 993 were mapped. These markers were distributed throughout 223 linkage groups, which were clustered in 18 homo(eo)logous groups (HGs), with a cumulative map length of 3,682.04 cM and an average marker density of 3.70 cM. We performed QTL mapping of four traits and found seven QTLs. Our results suggest the presence of a stable QTL across locations. Furthermore, QTLs to soluble solid content (BRIX) and fiber content (FIB) traits had markers linked to putative candidate genes. CONCLUSIONS: This study is the first to report the use of GBS for large-scale variant discovery and genotyping of a mapping population in sugarcane, providing several insights regarding the use of NGS data in a polyploid, non-model species. The use of GBS generated a large number of markers and still enabled ploidy and allelic dosage estimation. Moreover, we were able to identify seven QTLs, two of which had great potential for validation and future use for molecular breeding in sugarcane.

Genetic diversity and population structure of Saccharum hybrids.

Sugarcane breeding programs incorporate foreign material to broaden the genetic base, expanding the gene pool. In South America, the Inter-university Network for the Development of the Sugarcane Industry (RIDESA) and Estación Experimental Agroindustrial Obispo Colombres (EEAOC) sugarcane breeding programs from Brazil and Argentina, respectively, have never exchanged materials. In that sense, the knowledge of the genetic diversity and population structure among sugarcane genotypes of both germplasm banks, determined in a reliable way through their molecular profiles, will provide valuable information to select the best parental accessions for crossing aimed at the efficient introgression of desirable alleles. For that, the aim was to determine the genetic diversity and population structure of 96 Saccharum commercial hybrids from RIDESA and EEAOC sugarcane breeding programs by using TRAP, SSR and markers related to disease resistance (e.g. Bru1 and G1). Genetic structure was determined through genetic similarity analysis, analysis of molecular variance (AMOVA), Multidimensional scaling (MDS), and a Bayesian method. Average PIC values were 0.25 and 0.26, Ho values were 0.24 and 0.28, and He values were 0.25 and 0.28, for TRAP and SSR primers, respectively. Genetic similarity, MDS, and analysis of structure revealed that Brazilian and Argentinean genotypes clustered in two groups clearly differentiated, whereas AMOVA suggested that there is more variability within programs than between them. Regarding Bru1 markers, Brazilian genotypes showed high frequency of haplotype 1 (71.4%) whereas Argentinean genotypes showed high frequency of haplotype 4 (80.8%); haplotypes 1 and 4 are indicated for the presence and absence of the brown rust resistance gene (Bru1), respectively. Respecting the G1 marker, most of the evaluated genotypes (60.4%) showed the presence of the fragment, in a similar proportion for genotypes of both programs. In conclusion, the exchange of materials, at least the most diverse genotypes, between RIDESA and EEAOC breeding programs will allow extending the genetic base of their germplasm banks, and the knowledge of genetic diversity will help breeders to better manage crosses, increasing the probability of obtaining more productive varieties.

Novel Tools for Adjusting Spatial Variability in the Early Sugarcane Breeding Stage.

The detection of spatial variability in field trials has great potential for accelerating plant breeding progress due to the possibility of better controlling non-genetic variation. Therefore, we aimed to evaluate a digital soil mapping approach and a high-density soil sampling procedure for identifying and adjusting spatial dependence in the early sugarcane breeding stage. Two experiments were conducted in regions with different soil classifications. High-density sampling of soil physical and chemical properties was performed in a regular grid to investigate the structure of spatial variability. Soil apparent electrical conductivity (ECa) was measured in both experimental areas with an EM38-MK2® sensor. In addition, principal component analysis (PCA) was employed to reduce the dimensionality of the physical and chemical soil data sets. After conducting the PCA and obtaining different thematic maps, we determined each experimental plot's exact position within the field. Tons of cane per hectare (TCH) data for each experiment were obtained and analyzed using mixed linear models. When environmental covariates were considered, a previous forward model selection step was applied to incorporate the variables. The PCA based on high-density soil sampling data captured part of the total variability in the data for Experimental Area 1 and was suggested to be an efficient index to be incorporated as a covariate in the statistical model, reducing the experimental error (residual variation coefficient, CVe). When incorporated into the different statistical models, the ECa information increased the selection accuracy of the experimental genotypes. Therefore, we demonstrate that the genetic parameter increased when both approaches (spatial analysis and environmental covariates) were employed.

A genome-wide association study identified loci for yield component traits in sugarcane (Saccharum spp.).

Sugarcane (Saccharum spp.) has a complex genome with variable ploidy and frequent aneuploidy, which hampers the understanding of phenotype and genotype relations. Despite this complexity, genome-wide association studies (GWAS) may be used to identify favorable alleles for target traits in core collections and then assist breeders in better managing crosses and selecting superior genotypes in breeding populations. Therefore, in the present study, we used a diversity panel of sugarcane, called the Brazilian Panel of Sugarcane Genotypes (BPSG), with the following objectives: (i) estimate, through a mixed model, the adjusted means and genetic parameters of the five yield traits evaluated over two harvest years; (ii) detect population structure, linkage disequilibrium (LD) and genetic diversity using simple sequence repeat (SSR) markers; (iii) perform GWAS analysis to identify marker-trait associations (MTAs); and iv) annotate the sequences giving rise to SSR markers that had fragments associated with target traits to search for putative candidate genes. The phenotypic data analysis showed that the broad-sense heritability values were above 0.48 and 0.49 for the first and second harvests, respectively. The set of 100 SSR markers produced 1,483 fragments, of which 99.5% were polymorphic. These SSR fragments were useful to estimate the most likely number of subpopulations, found to be four, and the LD in BPSG, which was stronger in the first 15 cM and present to a large extension (65 cM). Genetic diversity analysis showed that, in general, the clustering of accessions within the subpopulations was in accordance with the pedigree information. GWAS performed through a multilocus mixed model revealed 23 MTAs, six, three, seven, four and three for soluble solid content, stalk height, stalk number, stalk weight and cane yield traits, respectively. These MTAs may be validated in other populations to support sugarcane breeding programs with introgression of favorable alleles and marker-assisted selection.

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.

Sugarcane improvement: how far can we go?

In recent years, efforts to improve sugarcane have focused on the development of biotechnology for this crop. It has become clear that sugarcane lacks tools for the biotechnological route of improvement and that the initial efforts in sequencing ESTs had limited impact for breeding. Until recently, the models used by breeders in statistical genetics approaches have been developed for diploid organisms, which are not ideal for a polyploid genome such as that of sugarcane. Breeding programs are dealing with decreasing yield gains. The contribution of multiple alleles to complex traits such as yield is a basic question underlining the breeding efforts that could only be addressed by the development of specific tools for this grass. However, functional genomics has progressed and gene expression profiling is leading to the definition of gene networks. The sequencing of the sugarcane genome, which is underway, will greatly contribute to numerous aspects of research on grasses. We expect that both the transgenic and the marker-assisted route for sugarcane improvement will contribute to increased sugar, stress tolerance, and higher yield and that the industry for years to come will be able to rely on sugarcane as the most productive energy crop.

Sugarcane (Saccharum X officinarum): A Reference Study for the Regulation of Genetically Modified Cultivars in Brazil.

Global interest in sugarcane has increased significantly in recent years due to its economic impact on sustainable energy production. Sugarcane breeding and better agronomic practices have contributed to a huge increase in sugarcane yield in the last 30 years. Additional increases in sugarcane yield are expected to result from the use of biotechnology tools in the near future. Genetically modified (GM) sugarcane that incorporates genes to increase resistance to biotic and abiotic stresses could play a major role in achieving this goal. However, to bring GM sugarcane to the market, it is necessary to follow a regulatory process that will evaluate the environmental and health impacts of this crop. The regulatory review process is usually accomplished through a comparison of the biology and composition of the GM cultivar and a non-GM counterpart. This review intends to provide information on non-GM sugarcane biology, genetics, breeding, agronomic management, processing, products and byproducts, as well as the current technologies used to develop GM sugarcane, with the aim of assisting regulators in the decision-making process regarding the commercial release of GM sugarcane cultivars.