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ThesisItem Open Access Metagenomic analysis of bacterial diversity in the rice rhizosphere of kole lands of Thrissur(Department of Plant Biotechnology, College of Agriculture, Vellanikkara, 2021) Athira Krishnan, L R; KAU; Girija, DKole wetlands of Kerala are a complex ecological system and are known for the higher productivity of rice. The Kole lands remain submerged under flood water for about six months in a year and this seasonal alteration gives it both terrestrial and water related properties which determine the ecosystem structure. Though several studies have been conducted for exploring the diversity of fishes, birds, flora, butterflies, etc., in Kole lands, no systematic studies have been made on rhizosphere microbial diversity. This study was intended to analyze the bacterial diversity in the rice rhizosphere ecosystem of Kole lands of Thrissur. Rhizosphere soil samples were collected from three locations of Kole lands of Thrissur viz. Puzhakkal (Pzk), Mullassery (Mls) and Cherpu (Chr) and analyzed for physico-chemical and biological properties. Culturable microflora was enumerated using serial dilution plate method for bacteria, fungi, actinomycetes, N- fixers, P, K and Zn-solubilizers. Twenty four predominant bacterial isolates were purified and screened for PGP activities including production of IAA and ammonia and phosphate solubilization. The bacterial diversity of the rhizosphere samples was analyzed by metagenomic library construction and sequencing of V3-V4 regions of the 16S rRNA gene, using Next Generation Sequencing (NGS) technology. The sequences thus obtained were analyzed for the Operational Taxonomic Units (OTUs) using MEGAN and MG- RAST server. The analysis of physico-chemical parameters showed a comparatively low pH in all the samples. An extreme low pH can reduce the availability of major and secondary nutrients in the soil. The sample Pzk showed higher content of organic C. Culturable microflora and microbial biomass C analysis also showed a slight increase in the sample Pzk. The soil organic C content and microbial biomass C are reported to be positively correlated. The microbial biomass C is the measure of the weight of the organisms present.The predominant bacterial phyla in the rice rhizosphere of Kole lands of Thrissur included Proteobacteria, Chloroflexi, Acidobacteria, Actinobacteria, Bacteroidetes and Nitrospirae. The bacterial population was found higher in the sample Puzhakkal and comparatively lower in the sample Chr. Phylum Proteobacteria was found to be the most predominant bacterial phylum in Pzk while, Chloroflexi was more predominant in Mls and Chr. The classes Acidobacteria and Ktedonobacteria were found dominant in the samples Mls and Chr and the Pzk sample was dominated by Acidobacteria and Deltaproteobacteria. The phylum level bacterial diversity was found highest in the sample Chr with 21 phyla while the genus level bacterial diversity was highest in the sample Mls. The abundance of genera Desulfobacca, Thermoanaerobaculum, Thioalkalispira, Anaerolinea, Ktedonobacter, Gemmatimonas, Puedolabrys, Sulfuricurvum, Syntrophobacter, Haliangium, Geobacter and Syntrophorhabdus was observed in the Kole land rice rhizosphere samples. Many of these genera are involved in geo-cycling of nutrients like Fe, S and Mn and a few are used in waste water treatment. The species- level bacterial diversity was found to be highest in the sample Mls as indicated by the Chao1 and observed species indices. The predominant archaeal phyla in the rice rhizosphere of Kole lands of Thrissur included Euryarchaeota, Crenarchaeota and Thaumarchaeota. Archaea are still an under- detected and little-studied part of the soil, so their full influence on global biogeochemical cycles remains largely unexplored. This study has thrown light on the diversity of bacterial and archaebacterial communities in the peculiar ecosystem of Kole lands of Thrissur. Many of the biofertilizer organisms like Azospirillum, Paenibacillus, Cellulosimicrobium and biocontrol agents like Bacillus and Pseudomonas could be detected, which could be cultured and used as potential acid tolerant biofertilizers and PGPR. Many of the ‘Unclassified’ genera could be novel bacteria and more research is needed to identify their taxonomic position and functional role in the ecosystem.ThesisItem Open Access Phytochemical profiling and genetic diversity analysis of Mangifere indica Linn. varieties of Kerala(Department of Biotechnology, College of Agriculture, Vellayani, 2020) Bona Sajimon; KAU; Rameshkumar, K BThe study entitled “Phytochemical profiling and genetic diversity analysis of Mangifera indica Linn. varieties in Kerala” was carried out at the Phytochemistry and Phytopharmacology Division of Jawaharlal Nehru Tropical Botanic Garden and Research Institute, Palode, Thiruvananthapuram during the academic year 2019 – 2020. The objective of the study was to map and authenticate selected local varieties of Mangifera indica in Kerala through phytochemical profiling of leaf volatile chemicals and the genetic diversity analysis using SCoT marker polymorphisms. Essential oils were obtained from the mature leaves of ten local mango varieties through hydrodistillation using a Clevenger-type apparatus and were analysed using GC-MS. A total of 55 volatile compounds ranging from 92.2 % to 98.0 % were identified from the ten varieties studied. Monoterpenes and sesquiterpenes were the major class of compounds among the identified volatiles. The prominent ones from this terpene classes include bicyclogermacrene, α-gurjunene, α-pinene, α-phellandrene, E-caryophyllene, terpinolene, δ-3-carene, limonene, α-humulene, germacrene D, β-selinene and germacrene B. While the statistical analysis of the varieties using their phytochemical composition clustered Vellari and Kilichundan as the nearest neighbours, Moovandan and Pulinji emerged as two distinct varieties from others in comparison. SCoT Primers proved to be a fine tool in studying the genetic diversity of M. indica varieties with an average polymorphism of 82% among the ten studied varieties. The varieties Kilichundan, Moovandan, Neelam and Kottoorkonam appeared as the ones with highest genetic similarity. Though the phytochemical and genetic diversities observed among the varieties are not directly linkable, the analyses helped to establish fine distinction between the varieties.ThesisItem Open Access Molecular marker development for cassava mosaic disease resistance using bioinformatics tools(Department of Plant Biotechnology, College of Agriculture, Vellayani, 2015) Ambu, Vijayan; KAU; Sreekumar, JThe study entitled “Molecular marker development for cassava mosaic disease resistance using bioinformatics tools” was conducted at ICAR-CTCRI, Sreekariyam, Thiruvananthapuram during October 2104 to October 2015. The objectives of the study included development and evaluation of various SNP and SSR prediction pipelines, computational prediction and characterization of SNP and SSR in cassava, verification of SNP and SSR markers for cassava mosaic disease (CMD) resistant and susceptible breeding lines. The preliminary data set for the identification of SSR and SNP markers was obtained from the EST section of NCBI and the cassava transcript sequences from the Phytozome. A total of 120461 sequences was classified into 20 cultivars. The dataset was reduced to 14336 sequences after several pre-processing and screening steps. The resulting sequences were assembled and aligned using CAP3 and 2088 contigs were obtained. SNPs and SSRs were predicted from these datasets using respective prediction tools. The SNP prediction tools such as QualitySNP and AutoSNP were compared for their performance. Analysis was performed to identify the tool with the ability to annotate and identify more viable nonsynonymous and synonymous SNPs. The SSR prediction tools such as MISA and SSRIT was compared for their performance. Analysis was performed to identify the tool having the ability to predict more viable SSRs and the ability to classify them as mono, di, tri, tetra, penta, hexa and poly SSRs. Using QualitySNP, thirty nonsynonymous SNPs and twenty-six synonymous SNPs were identified. Using MISA, n 217 mono SSRs, 132 di SSRs, 139 tri SSRs, 3 tetra SSRs, 1 penta SSRs, 3 hexa SSRs and 42 complex SSRs were identified. Five sequences from identified SNPs and SSRs which have high hit percentage were selected for validation and primer designing for CMD resistant genes. These primers were validated using 5 resistant and 5 susceptible cassava varieties. Among the 10 primers after validation in wet lab, one SNP (SNP896) and one SSR (SSR 2063) primer was able to clearly differentiate between the resistant and susceptible varieties which can be used as potential markers in the breeding program for screening CMD resistance in cassava.
