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Cost and time-efficient construction of a 3'-end mRNA library from unpurified bulk RNA in a single tube.
Choi, Jungwon; Hyun, Jungheun; Hyun, Jieun; Kim, Jae-Hee; Lee, Ji Hyun; Bang, Duhee.
Affiliation
  • Choi J; Department of Chemistry, Yonsei University, Seoul, Republic of Korea.
  • Hyun J; Department of Chemistry, Yonsei University, Seoul, Republic of Korea.
  • Hyun J; Department of Chemistry, Yonsei University, Seoul, Republic of Korea.
  • Kim JH; Department of Chemistry, Yonsei University, Seoul, Republic of Korea.
  • Lee JH; Department of Clinical Pharmacology and Therapeutics, College of Medicine, Kyung Hee University, Seoul, Republic of Korea. hyunihyuni@khu.ac.kr.
  • Bang D; Department of Biomedical Science and Technology, Kyung Hee University, Seoul, Republic of Korea. hyunihyuni@khu.ac.kr.
Exp Mol Med ; 56(2): 453-460, 2024 Feb.
Article in En | MEDLINE | ID: mdl-38413820
ABSTRACT
The major drawbacks of RNA sequencing (RNA-seq), a remarkably accurate transcriptome profiling method, is its high cost and poor scalability. Here, we report a highly scalable and cost-effective method for transcriptomics profiling called Bulk transcriptOme profiling of cell Lysate in a single poT (BOLT-seq), which is performed using unpurified bulk 3'-end mRNA in crude cell lysates. During BOLT-seq, RNA/DNA hybrids are directly subjected to tagmentation, and second-strand cDNA synthesis and RNA purification are omitted, allowing libraries to be constructed in 2 h of hands-on time. BOLT-seq was successfully used to cluster small molecule drugs based on their mechanisms of action and intended targets. BOLT-seq competes effectively with alternative library construction and transcriptome profiling methods.
Subject(s)

Full text: 1 Collection: 01-internacional Health context: 1_ASSA2030 Database: MEDLINE Main subject: RNA / Gene Expression Profiling Language: En Journal: Exp Mol Med Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Health context: 1_ASSA2030 Database: MEDLINE Main subject: RNA / Gene Expression Profiling Language: En Journal: Exp Mol Med Year: 2024 Document type: Article