Plant Resistance Gene, SNP and Genome Annotation an Overview
Abstract: Plants have developed systems of effective and passive protection to safeguard themselves from pathogens. Active processes include kinds of immune responses that are adaptive and intrinsic. Adaptive immunity is focused on reaction type RNAi and works primarily against viruses. Biological immunity is more general and allows the plant to protect itself against a wide range of pathogens through bacterial and model resistance receptors (PPRs) and forms of resistance (R proteins). PPRs identify molecular models associated with microbes or pathogen that are preserved in a specific category of pathogens. With such big marker amounts, it has become feasible to scan the entire genome for interactions of individual markers with particular quantitatively hereditary traits called whole-genome studies (WGS), genome-wide association trials (GWAS), or association genetics at exceptionally elevated marker densities. Several SNP recognition methods have been used in a specified plant to identify significant amounts of SNPs. These include: identification of SNP based on EST feature information; identification of SNP from sequenced genomes; re-sequencing of amplicons; identification of SNP using sequencing techniques of the next generation and identification of SNP based on cluster tests. Pathologic recognizes parts of Genbank completely annotated genome and MetaCyc has been used as a database for the reference pathway. In contrast to sequence similarity information used in other systems, Pathologic uses Genbank annotation information and the EC assignment as evidence of the presence of each pathway in the genome of interest reference database. When the matching task is finished, pathologic will infer a number of reactions expected to take place in the destination genome and will determine which one of those pathways in the target genome are likely to exist.
Keywords: identification / models / RNAi / proteins / annotation / adaptive / SNP / pathogens / annotated genome
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