Transcriptomic Analyses of Differential Host Responses to Red Rot Pathogen Colletotrichum Falcatum in Sugarcane Through Subtractive Library and NGS Approach

The fungal pathogen Colletotrichum falcatum causes the stalks, the economically important for sugar extraction. Although, disease management is achieved by cultivating resistant cultivars, the complex polyploidy of sugarcane genome complicates understanding the inheritance of disease resistance. Earlier attempts of using resistant and susceptible varieties to understand host-pathogen interaction resulted in cultivar specific expression of genes due to different genomic background of the varieties. To avoid host background variation in the interaction, suppression subtractive hybridization (SSH) based next generation sequencing technology was utilized in the same cv Co 7805 which behaves differently as incompatible and compatible to two different C. falcatum pathotypes. In the incompatible interaction (ICI) with C. falcatum pathotype Cf87012 (Less virulent, LVir) 10,038 contigs were assembled from ~54,699,263 raw reads. In the compatible interaction (CI) to the C. falcatum pathotype Cf94012 (Virulent, Vir) 4022 contigs were assembled from ~52,509,239 raw reads. The transcripts homologous to CEBiP receptor and transcripts involved in the signals ROS, Ca2+, BR, JA and ABA were exhibited in both the responses. Additionally, MAPK, ET, PI signals and JA amino conjugation related transcripts were found only in ICI. Finally, the temporal gene expression of a total number of 16 transcripts was monitored in qRT-PCR. Most of the transcripts exhibited highest induction in ICI in comparison with CI. Further, more than 17 transcripts specific to the pathogen were found only in CI, indicating that the pathogen colonizes the host tissue whereas it failed to to do so in ICI. Overall, this study has identified for the first time, the differential responses of a single sugarcane host to two different C. falcatum pathotypes and PAMP triggered immunity (PTI) is exhibited in both the responses, but the more efficient effector triggered immunity (ETI) was found only in ICI at the molecular level.

Molecular Characterization and Evaluation of Special Sugarcane Varieties Suitable for Co-Generation of Power

Sugarcane is a major agro-industrial crop in India. The fibre content in sugarcane is gaining importance as fuel for co-generation of electricity. Hence, the present study was proposed to genetically characterize and identify suitable clones for co-generation with high yielding, optimum sucrose per cent, erect, non-lodging and good ratooning ability characters. Genetic analysis of 10 sugarcane hybrids was carried out using STMS primers. Out of 110 markers amplified, 77.27 % were polymorphic with an average of 8.5 polymorphic products per STMS primer. Similarity coefficient value of 0.79 and 0.48 was detected with closely and distantly related hybrids respectively. The average genetic similarity among the hybrids was ~78.6%. These results indicated the existence of moderate level of genetic diversity among these high biomass hybrids. Evaluation trial in replicated randomized block design including five early and five mid late clones was conducted at Regional Agricultural Research Station (RARS), Anakapalle during 2007 to 2010. Early clones viz., CoA 03081 (123.0 t/ha and 14.93 t/ha), CoA 02081 (122.0 t/ha and 14.78 t/ha) and CoA 07321 (118.7 t/ha and 14.10 t/ha) were significantly superior for cane and CCS yields than the best standard Co 7508 (104.0 t/ha and 13.34 t/ha). Midlate clones viz., CoA 07322 (137.0 t/ha and 17.12 t/ha) and CoA 02082 (132.0 t/ha and 17.00 t/ha) were significantly superior over the standard CoV 92102 (125.0 t/ha and 16.95 t/ha) for cane and CCS yields. The fibre content of the early and midlate clones ranged from 18.67 (CoA 02081) to 22.50 (CoA 03081) and 20.17 (CoA 07322) to 23.00 (CoA 03082), respectively. These elite clones recorded resistant reaction to red rot disease. The results revealed the potential of these clones suitable for co-generation of power with high yielding, high fibre content, optimum sucrose per cent and good ratooning ability.

Rapid detection of red rot disease pathogens (Pythium chondricola/P. porphyrae) in Pyropia yezoensis (Rhodophyta) using PCR-RFLP method

Red rot disease is one of the most well-known algal diseases infecting red algae Pyropia species. This disease seriously decreases the quality and quantity of Pyropia aquaculture products in Korea, Japan, and China. Recently we first found that Pythium chondricola (Oomycetes) infecting blades of Pyropia yezoensis. Therefore two Pythium species (P. chondricola/P. porphyrae) have been reported as red rot disease pathogens. In this study, we developed a species-specific molecular marker for discriminating the two red rot disease pathogens. Using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method based on the mitochondrial cytochrome c oxidase subunit 2 (cox2) and nuclear ribosomal RNA large subunit (LSU) regions, these two Pythium species were successfully classified without a sequencing step. This new method showed high specificity and efficiency for detecting red rot disease pathogens at the species level for both of the cultured samples and field samples. Therefore the molecular markers developed in this study are effective for long-term monitoring on the infection and distribution pattern of each Pythium species in Pyropia aquaculture farms. Moreover, the molecular monitoring can provide useful information for predicting infection and preventing mass mortality of Pyropia species by red rot disease.

Phylogenetic Analysis and Genetic Diversity of Colletotrichum falcatum Isolates Causing Sugarcane Red Rot Disease in Bangladesh

Colletotrichum falcatum Went causes red rot disease in sugarcane farming in the tropical and sub-tropical regions. This disease causes significant economic loss to the sugarcane production industry. Successful disease management strategies depend on understanding the evolutionary relationship between pathogens, genetic diversity, and population structure, particularly at the intra-specific level. Forty-one isolates of C. falcatum were collected from different sugarcane farms across Bangladesh for molecular identification, phylogeny and genetic diversity study. The four genes namely, ITS-rDNA, β-tubulin, Actin and GAPDH sequences were conducted. All the 41 C. falcatum isolates showed a 99–100% similarity index to the conserved gene sequences in the GenBank database. The phylogram of the four genes revealed that C. falcatum isolates of Bangladesh clustered in the same clade and no distinct geographical structuring were evident within the clade. The four gene sequences revealed that C. falcatum isolates from Bangladesh differed from other countries´ isolates because of nucleotides substitution at different loci. The genetic structure of C. falcatum isolates were determined using ISSR marker generated 404 polymorphic loci from 10 selected markers. The percentage of polymorphic loci was 99.01. The genetic variability at species level was slightly higher than at population level. Total mean gene diversity at the species level was 0.1732 whereas at population level it was 0.1521. The cluster analysis divided 41 isolates into four main genetic groups and the principal component analysis was consistent with cluster analysis. To the best of our knowledge, this is the first finding on characterizing C. falcatum isolates infesting sugarcane in Bangladesh. The results of this present study provide important baseline information vis a vis C. falcatum phylogeny analysis and genetic diversity study.

Identification and Detection of Sugarcane Crop Disease Using Image Processing

Sugarcane is a renewable, natural agriculture resource and it is most important crop of India. Sugarcane Crop is a perennial crop which results into less labour and high yields. Sugarcane crop is one of the main pillar for Indian economy. Nowadays there are different diseases which affecting the sugarcane plants in diverse areas. So In this work we are going to use machine learning algorithms and image processing for sugarcane leaf disease detection. Machine learning is a trending area where the technological benefits can be imparted to the agriculture field also. In this we are going to use PCA algorithm which is one of the unsupervised machine learning algorithms. The dataset consists of 3 types of diseases. Total dataset is divided into various proportions of training and testing sets. There are various detection and classification techniques which are done using various algorithms at each stage but in PCA algorithm detection and classification is done by same algorithm which is PCA. The diseases of sugarcane consider in this project are red rot, smut, wilt.

Assessment of Sugarcane Genotypes for Red Rot Resistance and Antifungal Activity of Rhizosphere Microbiota against Colletotricum falcatum

The aim of this study was to screen the potential of locally grown sugarcane genotypes for red rot resistance and activity of native microbial strains against the pathogen. Field trials were conducted with 70 genotypes for consecutive years and results showed that only two genotypes viz., SSRI-1 and CO-0238 showed resistant behavior towards red rot of sugarcane. The red rot pathogen Colletotrichum falcatum Went was characterized and pathogenicity tests on two susceptible genotypes (NSG-59 and CPSG-2923) showed high virulence of SUCF04 isolate to develop severe disease lesions. The native rhizospheric microbiota was screened for microbial consortia exhibiting fine antifungal activity against the highly virulent pathogenic strain. The antagonism assay exposed that 10 bacterial isolates out of 46 showed great potential for antifungal activity. The selected bacterial isolates revealed 68–99% pathogen inhibition during the assay. The fungal strains with biological control potential inhibited the pathogen growth by 20–80% and a group of three strains with more than 50% antifungal activity were characterized. The molecular characterization of these microbes revealed that the isolates were belonging to Bacillus subtilus, Pseudomonas putida, Pseudomonas fluorescence, Trichoderma harzianum and several other important taxa. This study revealed that only two sugarcane genotypes were found as resistant against red rot pathogen, while most of the genotypes showed susceptible to moderately susceptible response. Moreover, the native residential microbiota associated with sugarcane exhibited great antifungal potential and can be utilized for disease protection and improved crop productivity. © 2021 Friends Science Publishers

Use of Liming and Incidence of Diseases in Sugarcane

This study aimed to evaluate the incidence of red rot, brown leaf spot, and smut in ten sugarcane genotypes during two consecutive cycles, in the absence and presence of limestone. The experimental design consisted of randomized blocks with four replications, in the presence and absence of liming in the following sugarcane genotypes: G1 (RB002754), G2 (RB021754), G3 (RB041443), G4 (RB863129), G5 (RB93509), G6 (RB951541), G7 (RB962962), G8 (RB992506), G9 (SP79-1011), and G10 (VAT90-212) for genotype x environment interaction. The lowest incidences of red rot were observed in G3 (RB041443), G4 (RB863129), G8 (RB992506), and G9 (SP79-1011) for plant cane, and in G3 (RB041443), G4 (RB863129), G5 (RB93509), G8 (RB992506), and G9 (SP79-1011) for ratoon. All genotypes were susceptible to Colletotrichum falcatum, but limestone reduced its incidence in G3 (RB041443), G6 (RB951541), and G10 (VAT90-212) during the first growth cycle, and in G1 (RB002754), G2 (RB021754), G5 (RB93509), G6 (RB951541), G7 (RB962962), and G10 (VAT90-212) in the ratoon crop. Liming also reduced the incidence of brown leaf spot in G4 (RB863129), G6 (RB951541), and G9 (SP79-1011) in plant cane and G6 (RB951541) and G7 (RB962962) in the ratoon crop. Only the G9 genotype (SP79-1011) showed an incidence of smut. The genotypes had different incidence levels of red rot, brown leaf spot, and smut diseases, which varied in the presence of limestone. Limestone use reduced disease incidence as a function of genotype and cutting cycle.