BaM-seq and TBaM-seq, highly multiplexed and targeted RNA-seq protocols for rapid, low-cost library generation from bacterial samples
Author(s)
Johnson, Grace E; Parker, Darren J; Lalanne, Jean-Benoit; Parker, Mirae L; Li, Gene-Wei
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<jats:title>Abstract</jats:title>
<jats:p>The ability to profile transcriptomes and characterize global gene expression changes has been greatly enabled by the development of RNA sequencing technologies (RNA-seq). However, the process of generating sequencing-compatible cDNA libraries from RNA samples can be time-consuming and expensive, especially for bacterial mRNAs which lack poly(A)-tails that are often used to streamline this process for eukaryotic samples. Compared to the increasing throughput and decreasing cost of sequencing, library preparation has had limited advances. Here, we describe bacterial-multiplexed-seq (BaM-seq), an approach that enables simple barcoding of many bacterial RNA samples that decreases the time and cost of library preparation. We also present targeted-bacterial-multiplexed-seq (TBaM-seq) that allows for differential expression analysis of specific gene panels with over 100-fold enrichment in read coverage. In addition, we introduce the concept of transcriptome redistribution based on TBaM-seq that dramatically reduces the required sequencing depth while still allowing for quantification of both highly and lowly abundant transcripts. These methods accurately measure gene expression changes with high technical reproducibility and agreement with gold standard, lower throughput approaches. Together, use of these library preparation protocols allows for fast, affordable generation of sequencing libraries.</jats:p>
Date issued
2023-01-10Department
Massachusetts Institute of Technology. Department of Biology; Massachusetts Institute of Technology. Department of PhysicsPublisher
Oxford University Press (OUP)
Citation
Johnson, Grace E, Parker, Darren J, Lalanne, Jean-Benoit, Parker, Mirae L and Li, Gene-Wei. 2023. "BaM-seq and TBaM-seq, highly multiplexed and targeted RNA-seq protocols for rapid, low-cost library generation from bacterial samples." 5 (1).
Version: Final published version
ISSN
2631-9268
Keywords
Applied Mathematics, Computer Science Applications, Genetics, Molecular Biology, Structural Biology