Determination of Morpho-Physiological Traits for Assessing Drought Tolerance in Sugarcane.

Drought is a significant constraint to sugarcane productivity. Therefore, understanding how different varieties of sugarcane respond to drought stress can facilitate breeding programs and set up criteria for selecting drought-tolerant varieties. In the present study, we examined eight morpho-physiological traits to distinguish 40 sugarcane genotypes categorized into four groups based on significant differences in cane yield under non-stressed conditions and reduction of cane yield under drought-stressed conditions. The study was conducted during the formative stage in a greenhouse, encompassing both control and drought conditions. Drought treatments resulted in significant changes and differences in the mean values of various morpho-physiological traits. The hierarchical clustering analysis, utilizing stay-green traits such as higher chlorophyll fluorescence ratio (Fv/Fm), leaf chlorophyll content (SPAD), leaf relative water content (RWC), and lower leaf rolling score (LR), leaf drying score (LD), and drought recovery score (DR), successfully grouped 40 sugarcane genotypes into four major clusters, similar to the previously categorized groups. Correlation analysis showed significant relationships among cane yield, reduction of cane yield under drought conditions, and the stay-green traits. Our results demonstrated that morpho-physiological traits contributing to the "stay-green" phenotypes could be useful as selection criteria for drought tolerance in sugarcane.

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

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

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

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

Candidate gene association of gene expression data in sugarcane contrasting for sucrose content.

Association mapping of gene expression data, generated from transcriptome and proteome studies, provides a means of understanding the functional significance and trait association potential of candidate genes. In this study, we applied candidate gene association mapping to validate sugarcane genes, using data from the starch and sucrose metabolism pathway, transcriptome, and proteome. We performed multiplex PCR targeted amplicon sequencing of 109 candidate genes, using NGS technology. A range of statistical models, both single-locus and multi-locus, were compared for minimization of false positives in association mapping of four sugar-related traits with different heritability. The Fixed and random model Circulating Probability Unification model effectively suppressed false positives for both low- and high-heritability traits. We identified favorable alleles of the candidate genes involved in signalling and transcriptional regulation. The results will support genetic improvement of sugarcane and may help clarify the genetic architecture of sugar-related traits.

Differential expression between drought-tolerant and drought-sensitive sugarcane under mild and moderate water stress as revealed by a comparative analysis of leaf transcriptome.

Sugarcane contributes 80% of global sugar production and to bioethanol generation for the bioenergy industry. Its productivity is threatened by drought that can cause up to 60% yield loss. This study used RNA-Seq to gain a better understanding of the underlying mechanism by which drought-tolerant sugarcane copes with water stress. We compared gene expression in KPS01-12 (drought-tolerant genotype) and UT12 (drought-sensitive genotype) that have significantly different yield loss rates under drought conditions. We treated KPS01-12 and UT12 with mild and moderate water stress and found differentially expressed genes in various biological processes. KPS01-12 had higher expression of genes that were involved in water retention, antioxidant secondary metabolite biosynthesis, and oxidative and osmotic stress response than UT12. In contrast, the sensitive genotype had more down-regulated genes that were involved in photosynthesis, carbon fixation and Calvin cycle than the tolerant genotype. Our obtained expression profiles suggest that the tolerant sugarcane has a more effective genetic response than the sensitive genotype at the initiation of drought stress. The knowledge gained from this study may be applied in breeding programs to improve sugarcane production in drought conditions.

Pan- and core- gene association networks: Integrative approaches to understanding biological regulation.

The rapid increase in transcriptome data provides an opportunity to access the complex regulatory mechanisms in cellular systems through gene association network (GAN). Nonetheless, GANs derived from single datasets generally allow us to envisage only one side of the regulatory network, even under the particular condition of study. The circumstance is well demonstrated by inconsistent GANs of individual datasets proposed for similar experimental conditions, which always leads to ambiguous interpretation. Here, pan- and core-gene association networks (pan- and core-GANs), analogous to the pan- and core-genome concepts, are proposed to increase the power of inference through the integration of multiple, diverse datasets. The core-GAN represents the consensus associations of genes that were inferred from all individual networks. On the other hand, the pan-GAN represents the extensive gene-gene associations that occurred in each individual network. The pan- and core-GANs prospects were demonstrated based on three time series microarray datasets in leaves of Arabidopsis thaliana grown under diurnal conditions. We showed the overall performance of pan- and core-GANs was more robust to the number of data points in gene expression data compared to the GANs inferred from individual datasets. In addition, the incorporation of multiple data broadened our understanding of the biological regulatory system. While the pan-GAN enabled us to observe the landscape of gene association system, core-GAN highlighted the basic gene-associations in essence of the regulation regulating starch metabolism in leaves of Arabidopsis.

Uncovering full-length transcript isoforms of sugarcane cultivar Khon Kaen 3 using single-molecule long-read sequencing.

BACKGROUND: Sugarcane is an important global food crop and energy resource. To facilitate the sugarcane improvement program, genome and gene information are important for studying traits at the molecular level. Most currently available transcriptome data for sugarcane were generated using second-generation sequencing platforms, which provide short reads. The de novo assembled transcripts from these data are limited in length, and hence may be incomplete and inaccurate, especially for long RNAs. METHODS: We generated a transcriptome dataset of leaf tissue from a commercial Thai sugarcane cultivar Khon Kaen 3 (KK3) using PacBio RS II single-molecule long-read sequencing by the Iso-Seq method. Short-read RNA-Seq data were generated from the same RNA sample using the Ion Proton platform for reducing base calling errors. RESULTS: A total of 119,339 error-corrected transcripts were generated with the N50 length of 3,611 bp, which is on average longer than any previously reported sugarcane transcriptome dataset. 110,253 sequences (92.4%) contain an open reading frame (ORF) of at least 300 bp long with ORF N50 of 1,416 bp. The mean lengths of 5' and 3' untranslated regions in 73,795 sequences with complete ORFs are 1,249 and 1,187 bp, respectively. 4,774 transcripts are putatively novel full-length transcripts which do not match with a previous Iso-Seq study of sugarcane. We annotated the functions of 68,962 putative full-length transcripts with at least 90% coverage when compared with homologous protein coding sequences in other plants. DISCUSSION: The new catalog of transcripts will be useful for genome annotation, identification of splicing variants, SNP identification, and other research pertaining to the sugarcane improvement program. The putatively novel transcripts suggest unique features of KK3, although more data from different tissues and stages of development are needed to establish a reference transcriptome of this cultivar.