Decode-seq: a practical approach to improve differential gene expression analysis

It is often the case that inadequate numbers of biological replicates are utilized in differential gene expression analysis. We describe an easy and effective RNA-seq approach using molecular barcoding to enable profiling a large number of replicates simultaneously. This approach significantly improved the performance of differential gene expression analysis. Using this approach in medaka fish (Oryzias latipes), we discovered novel genes with sexually dimorphic expression, and genes necessary for germ cell development. We appeal that the common practice of using three replicates in differential gene expression analysis should be abandoned. Overall design: Each library contains 20 to 60 barcoded samples, total 12 libraries and 360 barcoded samples. DE1-1, DE1-2, and DE1-3 contain replicates of mix4.5 (human RNA with 4.5% mouse RNA), mix1.5 (1.5% mouse RNA) and mix0.9 (0.9% mouse RNA), 100ng input RNA per sample DE2-2, DE2-3, DE2-4, and DE2-5 contain replicates of F (medaka female gonadal RNA), M (medaka male gonadal RNA) and D (DMY mutant male medaka RNA). DE3-3 and DE3-4 contain replicates of the same mixes as DE1, 10ng and 1ng input RNA per sample respectively DE8-6, DE8-12-1 and DE8-12-2 contain replicates of mix5 (human RNA with 5% mouse RNA) and mix1 (1% mouse RNA), 100ng input RNA per sample All libraries were constructed using the Decode-seq protocol we developed except DE8-6, which was constructed using the previous published BRB-seq protocol

Identifier
Source https://data.blue-cloud.org/search-details?step=~012FC898D8949B81051985AAD1E3914ADFE8067259C
Metadata Access https://data.blue-cloud.org/api/collections/FC898D8949B81051985AAD1E3914ADFE8067259C
Provenance
Instrument HiSeq X Ten; ILLUMINA
Publisher Blue-Cloud Data Discovery & Access service; ELIXIR-ENA
Contributor Institute of Genetics and Developmental Biology
Publication Year 2024
OpenAccess true
Contact blue-cloud-support(at)maris.nl
Representation
Discipline Marine Science
Temporal Point 2020-02-21T00:00:00Z