Baiting out a full length sequence from unmapped RNA-seq data

BMC Genomics

Qing Li¹  Lei Huang¹  Jing Luo¹  Yubo Zhang¹  Yanling Peng¹  Qitong Huang²  Dongwei Li³  Jikai Wen⁴ 

[1] Animal Functional Genomics Group, Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, 518120, Shenzhen, China;Animal Functional Genomics Group, Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, 518120, Shenzhen, China;Animal Breeding and Genomic, Wageningen University & Research, 6708PB, Wageningen, Netherlands;Animal Functional Genomics Group, Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, 518120, Shenzhen, China;Guangdong Provincial Key Laboratory of Protein Function and Regulation in Agricultural Organisms, College of Life Sciences, South China Agricultural University, 510642, Guangzhou, Guangdong, China;Guangdong Provincial Key Laboratory of Protein Function and Regulation in Agricultural Organisms, College of Life Sciences, South China Agricultural University, 510642, Guangzhou, Guangdong, China;

关键词: Unmapped reads;    Full length sequence;    Statistical model;    RNA-seq;   

DOI  :  10.1186/s12864-021-08146-4

来源: Springer

【 摘 要 】

BackgroundAs a powerful tool, RNA-Seq has been widely used in various studies. Usually, unmapped RNA-seq reads have been considered as useless and been trashed or ignored.ResultsWe 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 and randomly select one 149 bp read as a model. Specific reverse transcription primers are designed to amplify its both ends, followed by next generation sequencing. Then we design a statistical model based 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 1556 bp, with insertion mutations in microsatellite structure.ConclusionWe believe this method would be a useful strategy to extract the sequences information from the unmapped RNA-seq data. Further, it is an alternative way to get the full length sequence of unknown cDNA.

【 授权许可】

CC BY