Baiting out a full length sequence from unmapped RNA-seq data
收藏干细胞与再生医学数据中心2022-02-20 更新2024-03-06 收录
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资源简介：
Usually, unmapped reads have been considered as useless and been trashed or ignored. Here, we develop a strategy to mining the full length sequence by unmapped reads combining with specific reverse transcription primers design and high throughput sequencing. In this study, we salvage 36 unmapped reads from standard RNA-Seq data(GSM3188619) and randomly select one 149 bp read as a model(CTGGTGCCATAATTCAGGGAACTGTGTTCTTGATGTACTATCTGAGACATTTGTGCTTCCCCCCATCCAGCTATCAGGCTGTTAGGCAATGCACTTCTAGGAATTAGAATTCTATAAGGAATCTCATGCTGGAAGAACAAAAAGACCCA ). Specific reverse transcription primers(5' end:CTGGTGCCATAATTCAGGGA, 3' end:GGATCTTCACGTAACGGATTGT) are designed to amplify its both ends, followed by next generation sequencing. Then we use a statistical model base on power law distribution to estimate its integrality and significance. Further, we validate it by Sanger sequencing. The result shows that the full length is 1,556 bp, with InDel mutation in microsatellite structure. This would be a useful strategy to extract the sequences information from the unmapped RNA-seq data.
提供机构：
Shenzhen agricultural Genome Research Institute, Chinese Academy of Agricultural Sciences
创建时间：
2022-02-20
