Markers associated with stalk number and suckering in sugarcane colocate with tillering and rhizomatousness QTLs in sorghum

Applying Molecular Phenotyping Tools to Explore Sugarcane Carbon Potential

Sugarcane (Saccharum spp.), a C₄ grass, has a peculiar feature: it accumulates, gradient-wise, large amounts of carbon (C) as sucrose in its culms through a complex pathway. Apart from being a sustainable crop concerning C efficiency and bioenergetic yield per hectare, sugarcane is used as feedstock for producing ethanol, sugar, high-value compounds, and products (e.g., polymers and succinate), and bioelectricity, earning the title of the world's leading biomass crop. Commercial cultivars, hybrids bearing high levels of polyploidy, and aneuploidy, are selected from a large number of crosses among suitable parental genotypes followed by the cloning of superior individuals among the progeny. Traditionally, these classical breeding strategies have been favoring the selection of cultivars with high sucrose content and resistance to environmental stresses. A current paradigm change in sugarcane breeding programs aims to alter the balance of C partitioning as a means to provide more plasticity in the sustainable use of this biomass for metabolic engineering and green chemistry. The recently available sugarcane genetic assemblies powered by data science provide exciting perspectives to increase biomass, as the current sugarcane yield is roughly 20% of its predicted potential. Nowadays, several molecular phenotyping tools can be applied to meet the predicted sugarcane C potential, mainly targeting two competing pathways: sucrose production/storage and biomass accumulation. Here we discuss how molecular phenotyping can be a powerful tool to assist breeding programs and which strategies could be adopted depending on the desired final products. We also tackle the advances in genetic markers and mapping as well as how functional genomics and genetic transformation might be able to improve yield and saccharification rates. Finally, we review how "omics" advances are promising to speed up plant breeding and reach the unexplored potential of sugarcane in terms of sucrose and biomass production.

Role of NGS and SNP genotyping methods in sugarcane improvement programs

Sugarcane (Saccharum spp.) is one of the most economically significant crops because of its high sucrose content and it is a promising biomass feedstock for biofuel production. Sugarcane genome sequencing and analysis is a difficult task due to its heterozygosity and polyploidy. Long sequence read technologies, PacBio Single-Molecule Real-Time (SMRT) sequencing, the Illumina TruSeq, and the Oxford Nanopore sequencing could solve the problem of genome assembly. On the applications side, next generation sequencing (NGS) technologies played a major role in the discovery of single nucleotide polymorphism (SNP) and the development of low to high throughput genotyping platforms. The two mainstream high throughput genotyping platforms are the SNP microarray and genotyping by sequencing (GBS). This paper reviews the NGS in sugarcane genomics, genotyping methodologies, and the choice of these methods. Array-based SNP genotyping is robust, provides consistent SNPs, and relatively easier downstream data analysis. The GBS method identifies large scale SNPs across the germplasm. A combination of targeted GBS and array-based genotyping methods should be used to increase the accuracy of genomic selection and marker-assisted breeding.

Integration of sugarcane production technologies for enhanced cane and sugar productivity targeting to increase farmers' income: strategies and prospects

The idea of doubling the farmers' income in next 5 years has been slated by the Government of India. The specific target of increasing sugarcane farmers' income could be achieved by developing cost-effective technologies, transferring them from laboratory to land, educating the farmers and creating a linkage between all stakeholders. Consistent efforts shall be required to harness all possible sources for increasing farmer's income in and outside the agriculture sector with respect to improvement in sugarcane and sugar productivity, enhancement in resource use efficiency and adopting various other ways and means including intercropping, management of pests and diseases, use of biotechnological tools and minimizing post-harvest deterioration. The advances in sugarcane biotechnology could become remarkable in the coming years, both in terms of improving productivity as well as increasing the value and utility of this crop substantially. In future, genetically modified sugarcane varieties with increased resistance to different biotic and abiotic stresses would serve more towards sugarcane crop improvement. Any possibility of enhancement in the income of sugarcane farmers shall also be dependent upon the profitability and sustainability of the sugar industry. Integration of sugarcane production technologies for improvement in farm productivity, diversified sugarcane production system, reduced cost of cultivation along with increased processing plant efficiency and diversification to produce value added products shall ensure smooth and higher payment to the farmers. Development of low-cost technologies to convert "waste to resource" on a smaller scale shall also help the farmers to increase their income further. This paper focuses on possible measures to be taken up in each aspects of sugarcane cultivation including biotechnological approaches to achieve the goal of enhancing the income of sugarcane farmers substantially, particularly in the sub-tropical region of India.

Characterization of leaf transcriptome, development and utilization of unigenes-derived microsatellite markers in sugarcane (Saccharum sp. hybrid)

Sugarcane (Saccharum species hybrid) is the major source of sugar (> 80% sugar) in the world and is cultivated in more than 115 countries. It has recently gained attention as a source of biofuel (ethanol). Due to genomic complexity, the development of new genomic resources is imperative in understanding the gene regulation and function, and to fine tune the genetic improvement of sugarcane. In this study, a cDNA library was constructed from mature leaves so as to develop ESTs resources which were further compared with nucleotide and protein databases to explore the functional identity of sugarcane genes. The non-redundant ESTs (unigenes) were categorized into 18 metabolic functions. The major categories were bioenergetics and photosynthesis (4%), cell metabolism (5%), development related protein (3%), membrane-related, mobile genetic elements (5%), signal transduction (2%), DNA (1%), RNA (1%) and protein (2%) metabolism, other metabolic processes (3%), transcription factors (1%), transport (4%) and proteins related to stress/defense (4%). From 540 unique ESTs, 212 simple sequence repeats were identified, of which 206 were from 463 singlets and six were mined from 77 contig sequences. A total of 540 unique EST sequences were used for SSR search of which 97 (17.9%) contained specified SSR motifs, generating 212 unique SSRs. The genes characterized in this study and the EST-derived microsatellite markers identified from the cDNA library will enrich genomic resources for association- and linkage-mapping studies in sugarcane.

Potentials, Challenges, and Genetic and Genomic Resources for Sugarcane Biomass Improvement

Lignocellulosic biomass has become an emerging feedstock for second-generation bioethanol production. Sugarcane (Saccharum spp. hybrids), a very efficient perennial C4 plant with a high polyploid level and complex genome, is considered a top-notch candidate for biomass production due to its salient features viz. fast growth rate and abilities for high tillering, ratooning, and photosynthesis. Energy cane, an ideal type of sugarcane, has been bred specifically as a biomass crop. In this review, we described (1) biomass potentials of sugarcane and its underlying genetics, (2) challenges associated with biomass improvement such as large and complex genome, narrow gene pool in existing commercial cultivars, long breeding cycle, and non-synchronous flowering, (3) available genetic resources such as germplasm resources, and genomic and cell wall-related databases that facilitate biomass improvement, and (4) mining candidate genes controlling biomass in genomic databases. We extensively reviewed databases for biomass-related genes and their usefulness in biofuel generation. This review provides valuable resources for sugarcane breeders, geneticists, and broad scientific communities involved in bioenergy production.

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.

Multi-trait multi-environment quantitative trait loci mapping for a sugarcane commercial cross provides insights on the inheritance of important traits

Breeding trials typically consist of phenotypic observations for various traits evaluated in multiple environments. For sugarcane in particular, repeated measures are obtained for plant crop and one or more ratoons, such that joint analysis through mixed models for modeling heterogeneous genetic (co)variances between traits, locations and harvests is appropriate. This modeling approach also enables us to include molecular marker information, aiding in understanding the genetic architecture of quantitative traits. Our work aims at detecting QTL and QTL by environment interactions by fitting mixed models with multiple QTLs, with appropriate modeling of multi-trait multi-environment data for outcrossing species. We evaluated 100 individuals from a biparental cross at two locations and three  years for fiber content, sugar content (POL) and tonnes of cane per hectare (TCH). We detected 13 QTLs exhibiting QTL by location, QTL by harvest or the three-way interaction. Overall, 11 of the 13 effects presented some degree of pleiotropy, affecting at least two traits. Furthermore, these QTLs always affected fiber and TCH in the same direction, whereas POL was affected in the opposite way. There was no evidence in favor of the linked QTL over the pleiotropic QTL hypothesis for any detected genome position. These results provide valuable insights into the genetic basis of quantitative variation in sugarcane and the genetic relation between traits.

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive x additive interaction and QTL x environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0-26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL x environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.

Sugarcane for bioenergy production: an assessment of yield and regulation of sucrose content

An increasing number of plant scientists, including breeders, agronomists, physiologists and molecular biologists, are working towards the development of new and improved energy crops. Research is increasingly focused on how to design crops specifically for bioenergy production and increased biomass generation for biofuel purposes. The most important biofuel to date is bioethanol produced from sugars (sucrose and starch). Second generation bioethanol is also being targeted for studies to allow the use of the cell wall (lignocellulose) as a source of carbon. If a crop is to be used for bioenergy production, the crop should be high yielding, fast growing, low lignin content and requiring relatively small energy inputs for its growth and harvest. Obtaining high yields in nonprime agricultural land is a key for energy crop development to allow sustainability and avoid competition with food production. Sugarcane is the most efficient bioenergy crop of tropical and subtropical regions, and biotechnological tools for the improvement of this crop are advancing rapidly. We focus this review on the studies of sugarcane genes associated with sucrose content, biomass and cell wall metabolism and the preliminary physiological characterization of cultivars that contrast for sugar and biomass yield.

Genetic mapping in sugarcane, a high polyploid, using bi-parental progeny: identification of a gene controlling stalk colour and a new rust resistance gene

Modern sugarcane cultivars (Saccharum spp) are highly polyploïd and aneuploid interspecific hybrids (2n = 100-130). Two genetic maps were constructed using a population of 198 progeny from a cross between R570, a modern cultivar, and MQ76-53, an old Australian clone derived from a cross between Trojan (a modern cultivar) and SES528 (a wild Saccharum spontaneum clone). A total of 1,666 polymorphic markers were produced using 37 AFLP primer combinations, 46 SSRs and 9 RFLP probes. Linkage analysis led to the construction of 86 cosegregation groups for R570 and 105 cosegregation groups for MQ76-53 encompassing 424 and 536 single dose markers, respectively. The cumulative length of the R570 map was 3,144 cM, while that of the MQ76-53 map was 4,329 cM. Here, we integrated mapping information obtained on R570 in this study with that derived from a previous map based on a selfed R570 population. Two new genes controlling Mendelian traits were localized on the MQ76-53 map: a gene controlling the red stalk colour was linked at 6.5 cM to an AFLP marker and a new brown rust resistance gene was linked at 23 cM to an AFLP marker. Besides another previously identified brown rust resistance gene (Bru1), these two genes are the only other major genes to be identified in sugarcane so far.