1. KAUTIR (Kerala Agricultural University Theses Information and Retrieval)
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Item Prediction of SSR and SNP markers for anthracnose resiistance in YAM using bioinformatics tools and their validation(Department of Plant Biotechnology, College of Agriculture, Vellayani, 2018) Sahla, K; Sreekumar, JThe study entitled “Prediction of SSR and SNP markers for anthracnose resistance in yam using bioinformatics tools and their validation” was conducted at ICAR-Central Tuber Crop Research Institute, Sreekariyam, Thiruvananthapuram during October 2107 to August 2018. The objectives of the study is to computationally identify SNPs and SSRs for anthracnose resistance in Greater Yam and the verification of identified markers using resistant and susceptible varieties. The preliminary data set for the identification of SSR and SNP markers was obtained from the EST section of NCBI. A total of 44134 sequences was obtained. The dataset was reduced to 44114 sequences after several pre-processing and screening steps. The resulting sequences were assembled and aligned using CAP3 and 5940 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. For SSRs the SSR prediction tools such as MISA and SSRIT was compared and 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, 1789 nonsynonymous SNPs and 73 synonymous SNPs were identified. Using MISA, 359 mono SSRs, 268 di SSRs, 342 tri SSRs, 17 tetra SSRs, 7 penta SSRs, and 9 hexa SSRs were identified. Five sequences from identified SNPs and SSRs which having high hit percentage and low E value were selected for validation and primer designing for anthracnose resistant genes. These primers were validated using 3 resistant and 3 susceptible yam varieties. Among the primers after validation in wet lab, three SNPs (DaSNP1, DaSNP2, DaSNP3) and two SSRs (DaSSR1 and DaSSR2) 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 anthracnose resistance in yam.Item Molecular characterization of cassava mosaic disease (CMD) resistant varieties and wild relatives of cassava (Manihot esculenta Crantz) using SSR and SNP markers(Department of Plant Biotechnology, College of Agriculture, Vellayani, 2015) Dhanya, O G; Mohan, CIn the present study an attempt was made to estimate the extent of genetic diversity between 25 CMD resistant, 16 susceptible and seven wild relatives of cassava using 14 SSR and two SNP primers. Out of the 16 primers, nine primers was analysed using PAGE and remaining seven using capillary electrophoresis on genetic analyzer. The primers produced a total of 53 alleles across the 48 cassava accessions. NS198 was found to be highly polymorphic with 6 alleles followed by NS169, SSR36 and SSR39 (5allelles). The two SNP marker analysis on genetic analyzer namely SNPAPX3 and SNP ERF revealed that out of the two peaks generated, one of the peak at a range of 650-690 and 500-530bp respectively was common to all the 48 accessions and the other peak was variable between samples. The dendrogram constructed with 16 primers using UPGMA had four major clusters which clearly distinguished the resistant, susceptible and wild collections of cassava. The close observation made on one of the sub cluster within major resistant cluster revealed the resistant cultivars TME3 and TME4 were closely related with a similarity coefficient of 0.98. Clustering analysis was well supported by PCA, made representation of distinct location of CMD resistant, susceptible and wild relatives of cassava on 2D and 3D dimensions. Comparison of PIC value for all the 16 primers found out the PIC value for individual SSR markers is higher than the individual SNP PIC value at a range of 0.19 - 0.24. SSR PIC values ranged from 0.347 in SSR32 with observed heterozygosity (He) 0.447 to 0.72 in NS198 with He 0.76. Based on the PIC ranges NS198, NS169, SSRY39, RME-1, SSR106 and NS158 were selected as highly polymorphic markers.