Here we report a dynamic transcriptome landscape of medaka embryogenesis profiled by long-read RNA-seq, short-read RNA-seq, and ATAC-seq. Integrating these datasets, we constructed a much-improved gene model set including about 17,000 novel isoforms and identified 1600 transcription factors, 1100 long non-coding RNAs, and 150,000 potential cis-regulatory elements as well. We built a user-friend medaka omics data portal to present these datasets. This resource provides the first comprehensive omics datasets of medaka embryogenesis.

We term these three assays as the minimum ENCODE toolbox and propose the use of it as the initial and essential profiling genomic assays for model organisms that have limited data available. This work will be of great value for the research community using medaka as the model organism and many others as well.

Website:

• http://tulab.genetics.ac.cn/medaka_omics/

Citation:

• Li Y, Liu Y, Yang H, Zhang T, Naruse K, Tu Q. 2020. Dynamic transcriptional and chromatin accessibility landscape of medaka embryogenesis. Genome Res 30: 924–937. [DOI]

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.

Download:

• Experimental protocol (Updated: 2024/01)
• Computational scripts

Citation:

• Li Y, Yang H, Zhang H, Liu Y, Shang H, Zhao H, Zhang T, Tu Q. 2020. Decode-seq: a practical approach to improve differential gene expression analysis. Genome Biol 21: 66. [DOI]