Tm39Seq: A tagmentation-mediated 39 sequencing approach for improving scalability of RNAseq experiments

Luisa F. Pallares, Serge Picard, Julien F. Ayroles

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


RNA-seq has become the standard tool for collecting genome-wide expression data in diverse fields, from quantitative genetics and medical genomics to ecology and developmental biology. However, RNA-seq library preparation is still prohibitive for many laboratories. Recently, the field of single-cell transcriptomics has reduced costs and increased throughput by adopting early barcoding and pooling of individual samples —producing a single final library containing all samples. In contrast, RNA-seq protocols where each sample is processed individually are significantly more expensive and lower throughput than single-cell approaches. Yet, many projects depend on individual library generation to preserve important samples or for follow-up re-sequencing experiments. Improving on currently available RNA-seq methods we have developed TM39seq, a 39-enriched library preparation protocol that uses Tn5 transposase and preserves sample identity at each step. TM39seq is designed for high-throughput processing of individual samples (96 samples in 6h, with only 3h hands-on time) at a fraction of the cost of commercial kits ($1.5 per sample). The protocol was tested in a range of human and Drosophila melanogaster RNA samples, recovering transcriptomes of the same quality and reliability than the commercial NEBNext kit. We expect that the cost- and time-efficient features of TM39seq make large-scale RNA-seq experiments more permissive for the entire scientific community.

Original languageEnglish (US)
Pages (from-to)143-150
Number of pages8
JournalG3: Genes, Genomes, Genetics
Issue number1
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Genetics(clinical)
  • Genetics
  • Molecular Biology


  • RNAseq
  • TM3seq
  • TagSeq
  • Transcriptomics
  • mRNA extraction


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