Abstract
Brassica rapa L. (AA, 2n = 20), an A genome diploid species of Brassica genus is of researchers interest recent days since enormous amount of data is available about the genome. Since EST analysis is a powerful tool in gene discovery we compared different existing methods and developed a new pipeline for EST computational analysis to analyze the available data. A total of 1,438 expressed sequence tags sizing from 83 to 2,023 base pairs were generated and subjected to various types of analysis. Cluster analysis of these ESTs identified 969 unique sequences called unigenes, with 162 contigs and 807 singlets. Similarity search produced 704 significant hits with E-value ≥ 10−5. The functions of the best hits were annotated by gene ontology (GO) analysis. Additionally, we classified 293 and 541 unigenes based on their functions, using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein structural domain databases, respectively. We also identified and categorized 171 microsatellites into di-, tri-, tetra-, and penta nucleotide repeats, and designed primers. Possible open reading frames (ORFs) were predicted for 960 unigenes, by the comparison with a primary protein sequence database. In silico mapping of partial unigenes were done in bacterial artificial chromosome (BAC) sequences, downloaded from the Brassica genome project website. We determined 149 single nucleotide polymorphisms (SNPs) and 3 indels from the coding region of 27 unigenes of B. rapa and similar Brassica napus ESTs clusters. All the generated EST sequences were submitted to the GenBank EST database (dbEST) as accessions from CO749247 to CO750425.
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Dhandapani, V., Choi, S.R., Paul, P. et al. Development of EST database and transcriptome analysis in the leaves of Brassica rapa using a newly developed pipeline. Genes Genom 34, 671–679 (2012). https://doi.org/10.1007/s13258-012-0015-y
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DOI: https://doi.org/10.1007/s13258-012-0015-y