Identification of putative candidate genes for red rot resistance in sugarcane (Saccharum species hybrid) using LD-based association mapping

Genetic Engineering for Enhancing Sugarcane Tolerance to Biotic and Abiotic Stresses

Sugarcane, a vital cash crop, contributes significantly to the world's sugar supply and raw materials for biofuel production, playing a significant role in the global sugar industry. However, sustainable productivity is severely hampered by biotic and abiotic stressors. Genetic engineering has been used to transfer useful genes into sugarcane plants to improve desirable traits and has emerged as a basic and applied research method to maintain growth and productivity under different adverse environmental conditions. However, the use of transgenic approaches remains contentious and requires rigorous experimental methods to address biosafety challenges. Clustered regularly interspaced short palindromic repeat (CRISPR) mediated genome editing technology is growing rapidly and may revolutionize sugarcane production. This review aims to explore innovative genetic engineering techniques and their successful application in developing sugarcane cultivars with enhanced resistance to biotic and abiotic stresses to produce superior sugarcane cultivars.

Unveiling the predominance of Saccharum spontaneum alleles for resistance to orange rust in sugarcane using genome-wide association

KEY MESSAGE

Six QTLs of resistance to sugarcane orange rust were identified in modern interspecific hybrids by GWAS. For five of them, the resistance alleles originated from S. spontaneum. Altogether, they efficiently predict disease resistance. Sugarcane orange rust (SOR) is a threatening emerging disease in many sugarcane industries worldwide. Improving the genetic resistance of commercial cultivars remains the most promising solution to control this disease. In this study, an association panel of 568 modern interspecific sugarcane hybrids (Saccharum officinarum x S. spontaneum) from Réunion's breeding program was evaluated for its resistance to SOR under natural conditions of infection. Two genome-wide association studies (GWAS) were conducted between disease reactions and 183,842 single nucleotide polymorphism (SNP) markers obtained by targeted genotyping-by-sequencing. Five resistance quantitative trait loci (QTLs), named Oru1, Oru2, Oru3, Oru4 and Oru5, were identified using a single-locus GWAS (SL-GWAS). These five QTLs all originated from the species S. spontaneum. A multi-locus GWAS (ML-GWAS) uncovered an additional but less significant resistance QTL named Oru6, which originated from S. officinarum. All six QTLs had a moderate to major phenotypic effect on disease resistance. Prediction accuracy estimated with linear regression models based on each of the five QTLs identified by SL-GWAS was between 0.16-0.41. Altogether, these five QTLs provided a relatively high prediction accuracy of 0.60. In comparison, accuracies obtained with six genome-wide prediction models (i.e., GBLUP, Bayes-A, Bayes-B, Bayes-C, Bayesian Lasso and RKHS) reached only 0.65. The good prediction accuracy of disease resistance provided by the QTLs and the predominant S. spontaneum origin of their resistance alleles pave the way for effective marker-assisted breeding strategies.

A quality detection method of corn based on spectral technology and deep learning model

Corn is an important food crop in the world. With economic development and population growth, the nutritional quality of corn is of great significance to high-quality breeding, scientific cultivation and fine management. Aiming at the problems of cumbersome steps, time-consuming and laborious, and low accuracy in the current research on corn quality detection. This paper proposes to combine near-infrared (NIR) spectroscopy technology with deep learning technology to build a corn quality detection model based on convolutional neural network (LeNet-5). The original spectral data were preprocessed by wavelet transform (WT) and multivariate scattering correction (MSC) to remove noise interference and spectral scattering information. The Competitive Adaptive Reweighted Sampling Algorithm (CARS) was applied to optimize the characteristic wavenumber and reduce redundant data. According to the optimized characteristic wave number, it was input into the constructed corn quality detection model for simulation test, and the average detection accuracy rate of the test set was 96.46%, the average precision rate was 95.42%, the average recall rate was 97.92%, the average F1score was 96.64%, and the average recognition time was 51.95 s. Compared with traditional machine learning models such as BP neural network, K Nearest Neighbor (KNN), Support Vector Machine (SVM), Generalized Linear Model (GLM), Linear Discriminant Analysis (LDA), and Naive Bayesian (NB), the deep learning LeNet-5 network model constructed in this paper has an average accuracy increase of 39.32%, and has a higher detection accuracy.

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.

A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane

The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for genomics-assisted breeding (GAB). A replicated field trial was conducted for three crop cycles (plant cane, first ratoon, and second ratoon) using 432 sugarcane clones and used for conducting genome-wide association and genomic prediction of five sugar and yield component traits of the RA. The RA traits for economic index (EI), stalk population (SP), stalk weight (SW), tonns of cane per hectare (TCH), and tonns of sucrose per hectare (TSH) were estimated from the yield and sugar data. A total of six putative quantitative trait loci and eight nonredundant single-nucleotide polymorphism (SNP) markers were associated with all five tested RA traits and appear to be unique. Seven putative candidate genes were colocated with significant SNPs associated with the five RA traits. The genomic prediction accuracies for those tested traits were moderate and ranged from 0.21 to 0.36. However, the models fitting fixed effects for the most significant associated markers for each respective trait did not give any advantages over the standard models without fixed effects. As a result of this study, more robust markers could be used in the future for clone selection in sugarcane, potentially helping resolve the genetic control of the RA in sugarcane.

QTL mapping and identification of candidate genes linked to red rot resistance in sugarcane

Sugarcane (Saccharum species hybrid) is one of the most important commercial crops cultivated worldwide for products like white sugar, bagasse, ethanol, etc. Red rot is a major sugarcane disease caused by a hemi-biotrophic fungus, Colletotrichum falcatum Went., which can potentially cause a reduction in yield up to 100%. Breeding for red rot-resistant sugarcane varieties has become cumbersome due to its complex genome and frequent generation of new pathotypes of red rot fungus. In the present study, a genetic linkage map was developed using a selfed population of a popular sugarcane variety CoS 96268. A QTL linked to red rot resistance (qREDROT) was identified, which explained 26% of the total phenotypic variation for the trait. A genotype-phenotype network analysis performed to account for epistatic interactions, identified the key markers involved in red rot resistance. The differential expression of the genes located in the genomic region between the two flanking markers of the qREDROT as well as in the vicinity of the markers identified through the genotype-phenotype network analysis in a set of contrasting genotypes for red rot infection further confirmed the mapping results. Further, the expression analysis revealed that the plant defense-related gene coding 26S protease regulatory subunit is strongly associated with the red rot resistance. The findings can help in the screening of disease resistant genotypes for developing red rot-resistant varieties of sugarcane.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03481-7.

A Genome-Wide Association Study and Genomic Prediction for Fiber and Sucrose Contents in a Mapping Population of LCP 85-384 Sugarcane

Sugarcane (Saccharum spp. hybrids) is an economically important crop for both sugar and biofuel industries. Fiber and sucrose contents are the two most critical quantitative traits in sugarcane breeding that require multiple-year and multiple-location evaluations. Marker-assisted selection (MAS) could significantly reduce the time and cost of developing new sugarcane varieties. The objectives of this study were to conduct a genome-wide association study (GWAS) to identify DNA markers associated with fiber and sucrose contents and to perform genomic prediction (GP) for the two traits. Fiber and sucrose data were collected from 237 self-pollinated progenies of LCP 85-384, the most popular Louisiana sugarcane cultivar from 1999 to 2007. The GWAS was performed using 1310 polymorphic DNA marker alleles with three models of TASSEL 5, single marker regression (SMR), general linear model (GLM) and mixed linear model (MLM), and the fixed and random model circulating probability unification (FarmCPU) of R package. The results showed that 13 and 9 markers were associated with fiber and sucrose contents, respectively. The GP was performed by cross-prediction with five models, ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB) and Bayesian least absolute shrinkage and selection operator (BL). The accuracy of GP varied from 55.8% to 58.9% for fiber content and 54.6% to 57.2% for sucrose content. Upon validation, these markers can be applied in MAS and genomic selection (GS) to select superior sugarcane with good fiber and high sucrose contents.

Identification of QTLs and critical genes related to sugarcane mosaic disease resistance

Mosaic viral diseases affect sugarcane productivity worldwide. Mining disease resistance-associated molecular markers or genes is a key component of disease resistance breeding programs. In the present study, 285 F₁ progeny were produced from a cross between Yuetang 93-159, a moderately resistant variety, and ROC22, a highly susceptible variety. The mosaic disease symptoms of these progenies, with ROC22 as the control, were surveyed by natural infection under 11 different environmental conditions in the field and by artificial infections with a mixed sugarcane mosaic virus (SCMV) and sorghum mosaic virus (SrMV) inoculum. Analysis of consolidated survey data enabled the identification of 29 immune, 55 highly resistant, 70 moderately resistant, 62 susceptible, and 40 highly susceptible progenies. The disease response data and a high-quality SNP genetic map were used in quantitative trait locus (QTL) mapping. The results showed that the correlation coefficients (0.26~0.91) between mosaic disease resistance and test environments were significant (p< 0.001), and that mosaic disease resistance was a highly heritable quantitative trait (H² = 0.85). Seven mosaic resistance QTLs were located to the SNP genetic map, each QTL accounted for 3.57% ~ 17.10% of the phenotypic variation explained (PVE). Furthermore, 110 pathogen response genes and 69 transcription factors were identified in the QTLs interval. The expression levels of nine genes (Soffic.07G0015370-1P, Soffic.09G0015410-2T, Soffic.09G0016460-1T, Soffic.09G0016460-1P, Soffic.09G0017080-3C, Soffic.09G0018730-3P, Soffic.09G0018730-3C, Soffic.09G0019920-3C and Soffic.03G0019710-2C) were significantly different between resistant and susceptible progenies, indicating their key roles in sugarcane resistance to SCMV and SrMV infection. The seven QTLs and nine genes can provide a certain scientific reference to help sugarcane breeders develop varieties resistant to mosaic diseases.

Combining genomic selection with genome-wide association analysis identified a large-effect QTL and improved selection for red rot resistance in sugarcane

Red rot caused by the fungus Colletotrichum falcatum is the main disease limiting sugarcane productivity in several countries including the major producer India. The genetic basis for red rot resistance is unclear. We studied a panel of 305 sugarcane clones from the Australian breeding program for disease response phenotype and genotype using an Affymetrix® Axiom® array, to better understand the genetic basis of red rot resistance. SNP markers highly significantly associated with red rot response (≤ 10-8) were identified. Markers with largest effect were located in a single 14.6 Mb genomic region of sorghum (the closest diploid relative of sugarcane with a sequenced genome) suggesting the presence of a major-effect QTL. By genomic selection, the estimated selection accuracy was ~0.42 for red rot resistance. This was increased to ~0.5 with the addition of 29 highly significant SNPs as fixed effects. Analysis of genes nearby the markers linked to the QTL revealed many biotic stress responsive genes within this QTL, with the most significant SNP co-locating with a cluster of four chitinase A genes. The SNP markers identified here could be used to predict red rot resistance with high accuracy at any stage in the sugarcane breeding program.

Identification of potential MTAs and candidate genes for juice quality- and yield-related traits in Saccharum clones: a genome-wide association and comparative genomic study

Sugarcane is an economically important commercial crop which provides raw material for the production of sugar, jaggery, bioethanol, biomass and other by-products. Sugarcane breeding till today heavily relies on conventional breeding approaches which is time consuming, laborious and costly. Integration of marker-assisted selection (MAS) in sugarcane genetic improvement programs for difficult to select traits like sucrose content, resistance to pests and diseases and tolerance to abiotic stresses will accelerate varietal development. In the present study, association mapping approach was used to identify QTLs and genes associated with sucrose and other important yield-contributing traits. A mapping panel of 110 diverse sugarcane genotypes and 148 microsatellite primers were used for structured association mapping study. An optimal subpopulation number (ΔK) of 5 was identified by structure analysis. GWAS analysis using TASSEL identified a total of 110 MTAs which were localized into 27 QTLs by GLM and MLM (Q + K, PC + K) approaches. Among the 24 QTLs sequenced, 12 were able to identify potential candidate genes, viz., starch branching enzyme, starch synthase 4, sugar transporters and G3P-DH related to carbohydrate metabolism and hormone pathway-related genes ethylene insensitive 3-like 1, reversion to ethylene sensitive1-like, and auxin response factor associated to juice quality- and yield-related traits. Six markers, NKS 5_185, SCB 270_144, SCB 370_256, NKS 46_176 and UGSM 648_245, associated with juice quality traits and marker SMC31CUQ_304 associated with NMC were validated and identified as significantly associated to the traits by one-way ANOVA analysis. In conclusion, 24 potential QTLs identified in the present study could be used in sugarcane breeding programs after further validation in larger population. The candidate genes from carbohydrate and hormone response pathway presented in this study could be manipulated with genome editing approaches to further improve sugarcane crop.

Quantitative Trait Loci Mapping and Development of KASP Marker Smut Screening Assay Using High-Density Genetic Map and Bulked Segregant RNA Sequencing in Sugarcane (Saccharum spp.)

Sugarcane is one of the most important industrial crops globally. It is the second largest source of bioethanol, and a major crop for biomass-derived electricity and sugar worldwide. Smut, caused by Sporisorium scitamineum, is a major sugarcane disease in many countries, and is managed by smut-resistant varieties. In China, smut remains the single largest constraint for sugarcane production, and consequently it impacts the value of sugarcane as an energy feedstock. Quantitative trait loci (QTLs) associated with smut resistance and linked diagnostic markers are valuable tools for smut resistance breeding. Here, we developed an F1 population (192 progeny) by crossing two sugarcane varieties with contrasting smut resistance and used for genome-wide single nucleotide polymorphism (SNP) discovery and mapping, using a high-throughput genotyping method called "specific locus amplified fragment sequencing (SLAF-seq) and bulked-segregant RNA sequencing (BSR-seq). SLAF-seq generated 148,500 polymorphic SNP markers. Using SNP and previously identified SSR markers, an integrated genetic map with an average 1.96 cM marker interval was produced. With this genetic map and smut resistance scores of the F1 individuals from four crop years, 21 major QTLs were mapped, with a phenotypic variance explanation (PVE) > 8.0%. Among them, 10 QTLs were stable (repeatable) with PVEs ranging from 8.0 to 81.7%. Further, four QTLs were detected based on BSR-seq analysis. aligning major QTLs with the genome of a sugarcane progenitor Saccharum spontaneum, six markers were found co-localized. Markers located in QTLs and functional annotation of BSR-seq-derived unigenes helped identify four disease resistance candidate genes located in major QTLs. 77 SNPs from major QTLs were then converted to Kompetitive Allele-Specific PCR (KASP) markers, of which five were highly significantly linked to smut resistance. The co-localized QTLs, candidate resistance genes, and KASP markers identified in this study provide practically useful tools for marker-assisted sugarcane smut resistance breeding.

Utilization of a Sugarcane100K Single Nucleotide Polymorphisms Microarray-Derived High-Density Genetic Map in Quantitative Trait Loci Mapping and Function Role Prediction of Genes Related to Chlorophyll Content in Sugarcane

Chlorophyll is the most important pigment for plant photosynthesis that plays an important role in crop growth and production. In this study, the chlorophyll content trait was explored to improve sugarcane yield. Two hundred and eighty-five F₁ progenies from the cross YT93-159 × ROC22 with significantly different chlorophyll contents were included as test materials. The chlorophyll content of the +1 leaves during elongation phase was measured using a SPAD-502 meter through a three-crop cycle (plant cane, first ratoon, and second ratoon). Linkage analysis was conducted on a high-density genetic map constructed based on the sugarcane 100K SNP chip. In addition, Fv/Fm, plant height, stalk diameter, brix data were collected on plant cane during the elongation and maturation phases. The results showed that the +1 leaf SPAD values, which can be used as an important reference to evaluate the growth potential of sugarcane, were significantly and positively correlated with the Fv/Fm during elongation phase, as well as with plant height, stalk diameter, and brix during maturity phase (P < 0.01). The broad sense heritability (H ²) of the chlorophyll content trait was 0.66 for plant cane crop, 0.67 for first ratoon crop, and 0.73 for second ratoon crop, respectively, indicating that this trait was mainly controlled by genetic factors. Thirty-one quantitative trait loci (QTL) were detected by QTL mapping. Among them, a major QTL, qCC-R1, could account for 12.95% of phenotypic variation explained (PVE), and the other 30 minor QTLs explained 2.37-7.99% PVE. Twenty candidate genes related to chlorophyll content were identified in the QTLs plus a 200-Kb extension region within either sides, of which four were homologous genes involved in the chlorophyll synthesis process and the remaining 16 played a certain role in chlorophyll catabolic pathway, chloroplast organization, or photosynthesis. These results provide a theoretical reference for analyzing the genetic mechanism of chlorophyll synthesis and subsequent improvement of photosynthetic characteristics in sugarcane.

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.

Red rot of sugarcane (Colletotrichum falcatumWent)

Red rot of sugarcane was recorded more than 100 years before in Java, India, Argentina, USA and other countries, and it is one of the most devastating diseases of sugarcane. Since the cultivated sugarcane (Saccharum officinarum) has failed across the countries, systematic inter-specific hybridization betweenS. officinarumand the wild speciesS. spontaneumreferred as ‘nobilization’ was done to develop resistant varieties and the disease was managed in most of the countries. However, in the countries especially in Asia, varietal breakdown to red rot caused severe epiphytotics, by which the resistant varieties failed in the field at regular intervals. New pathogenic strains ofColletotrichum falcatumwith higher virulence were found responsible for varietal breakdown in sugarcane. Extensive cultivation of a single variety over large areas led to extensive crop damages due to ‘vertifolia’ effect in different decades in India. The current epiphytotic on the ruling variety Co 0238 has caused loss of more than one billion US dollars in the current season in the country. Detailed studies were done on pathogenic variation, epidemiology, screening methods, disease resistance mechanism, identifying effectors, pathogenicity determinants, antifungal genes and transgenics. Recently, complete genome and transcriptomes ofC. falcatumwere sequenced and pathogenicity hot spots and candidate secreted effector proteins were identified and this will further help to identify the candidate genes for further genetic manipulation. In spite of poor understanding on inheritance of resistance toC. falcatumin sugarcane, new varieties with red rot resistance were developed and deployed after each of the epiphytotic to save the crop. Further, other management practices including bioagents, chemicals and inducers were attempted and improved efficacy by mechanized sett treatment showed promising results to manage the disease under field conditions.

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.

Genetic diversity and population structure analysis of Saccharum and Erianthus genera using microsatellite (SSR) markers

In order to understand the genetic diversity and structure within and between the genera of Saccharum and Erianthus, 79 accessions from five species (S. officinarum, S. spontaneum, S. robustum, S. barberi, S. sinense), six accessions of E. arundinaceus, and 30 Saccharum spp. hybrids were analyzed using 21 pairs of fluorescence-labeled highly poloymorphic SSR primers and a capillary electrophoresis (CE) detection system. A total of 167 polymorphic SSR alleles were identified by CE with a mean value of polymorphic information content (PIC) of 0.92. Genetic diversity parameters among these 115 accessions revealed that Saccharum spp. hybrids were more diverse than those of Saccharum and Erianthus species. Based on the SSR data, the 115 accessions were classified into seven main phylogenetic groups, which corresponded to the Saccharum and Erianthus genera through phylogenetic analysis and principle component analysis (PCA). We propose that seven core SSR primer pairs, namely, SMC31CUQ, SMC336BS, SMC597CS, SMC703BS, SMC24DUQ, mSSCIR3, and mSSCIR43, may have a wide appicability in genotype identification of Saccharum species and Saccharum spp. hybrids. Thus, the information from this study contibites to manage sugarcane genetic resources.

Genome-wide association mapping identifies markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection

Sugarcane is an economically important crop for both food and biofuel industries. Marker-assisted breeding in sugarcane is becoming a reality with the recent development and deployment of markers linked with disease resistance genes. Large linkage disequilibrium in sugarcane makes genome-wide association studies (GWAS) a better alternative to biparental mapping to identify markers associated with agronomic traits. GWAS was conducted on a Louisiana core collection to identify marker-trait associations (MTA) for 11 cane yield and sucrose traits using single nucleotide polymorphism (SNP) and insertion-deletion (Indel) markers. Significant (P < .05) MTAs were identified for all traits where the top ranked markers explained up to 15% of the total phenotypic variation. High correlations (0.732 to 0.999) were observed between sucrose traits and 56 markers were found consistent across multiple traits. These markers following validation in more diverse populations could be used in marker-assisted selection of clones in sugarcane breeding program in Louisiana and elsewhere.

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.

Detection and validation of EST-SSR markers associated with sugar-related traits in sugarcane using linkage and association mapping

Sugar-related traits are of great importance in sugarcane breeding. In the present study, quantitative trait loci (QTL) mapping validated with association mapping was used to identify expressed sequence tag-simple sequence repeats (EST-SSRs) associated with sugar-related traits. For linkage mapping, 524 EST-SSRs, 241 Amplified Fragment Length Polymorphisms, and 10 genomic SSR markers were mapped using 283 F₁ progenies derived from an interspecific cross. Six regions were identified using Multiple QTL Mapping, and 14 unlinked markers using single marker analysis. Association analysis was performed on a set of 200 accessions, based on the mixed linear model. Validation of the EST-SSR markers using association mapping within the target QTL genomic regions identified two EST-SSR markers showing a putative relationship with uridine diphosphate (UDP) glycosyltransferase, and beta-amylase, which are associated with pol and sugar yield. These functional markers can be used for marker-assisted selection of sugarcane.

Red rot resistant transgenic sugarcane developed through expression of β-1,3-glucanase gene

Sugarcane (Saccharum spp.) is a commercially important crop, vulnerable to fungal disease red rot caused by Colletotrichum falcatum Went. The pathogen attacks sucrose accumulating parenchyma cells of cane stalk leading to severe losses in cane yield and sugar recovery. We report development of red rot resistant transgenic sugarcane through expression of β-1,3-glucanase gene from Trichoderma spp. The transgene integration and its expression were confirmed by quantitative reverse transcription-PCR in first clonal generation raised from T0 plants revealing up to 4.4-fold higher expression, in comparison to non-transgenic sugarcane. Bioassay of transgenic plants with two virulent C. falcatum pathotypes, Cf 08 and Cf 09 causing red rot disease demonstrated that some plants were resistant to Cf 08 and moderately resistant to Cf 09. The electron micrographs of sucrose storing stalk parenchyma cells from these plants displayed characteristic sucrose-filled cells inhibiting Cf 08 hyphae and lysis of Cf 09 hyphae; in contrast, the cells of susceptible plants were sucrose depleted and prone to both the pathotypes. The transgene expression was up-regulated (up to 2.0-fold in leaves and 5.0-fold in roots) after infection, as compared to before infection in resistant plants. The transgene was successfully transmitted to second clonal generation raised from resistant transgenic plants. β-1,3-glucanase protein structural model revealed that active sites Glutamate 628 and Aspartate 569 of the catalytic domain acted as proton donor and nucleophile having role in cleaving β-1,3-glycosidic bonds and pathogen hyphal lysis.

Identification of marker-trait associations for morphological descriptors and yield component traits in sugarcane

Ninety two sugarcane varieties from sub-tropical India were subjected to molecular profiling with 174 simple sequence repeat markers and characterized for 23 qualitative (morphological descriptors) and nine quantitative traits that directly or indirectly contribute to yield and juice quality. Using STRUCTURE-based population stratification study and a mixed linear model for marker-trait association (MTA) analysis, a total of 60 MTAs were identified for 22 qualitative traits that were able to explain a significantly higher (up to 40%) proportion of the phenotypic variations compared to all the previous reports of MTA studies in sugarcane. In addition, 21 MTAs stable over the three years of study were also identified for nine quantitative traits that explained 16-37% of the total trait variation. It could be concluded that the qualitative traits that are governed mostly by one or a few genes are more responsive to MTA studies and hence have a better potential to be adopted in marker-assisted breeding programmes in sugarcane. The MTAs identified in this study could also find significant applications in upcoming more stringent IP regime, which may necessitate tracking of specific alleles integrated in breeding programmes.