Figure 2 – Boxplots showing the variation in gene expression for the eight stages of fruit fly development. E3 is the phylotypic stage where there is the lowest variability in gene expression compared to earlier and later stages. Figure modified from Liu et al., 2020.
Then, the level of histone modifications over gene promoters was determined and used alongside BRB-seq gene expression data. This allowed the authors to investigate the potential mechanisms that regulate gene expression at different embryonic stages.
The combined analysis showed that histone modification signals were higher at the phylotypic stage, suggesting that histone modifications may limit gene expression variability at the mid-point in development.
How the large number of samples contributed to the results:
The initial large number of samples accounted for some eggs not being fertilized. Of 239 multiplexed BRB-seq samples, two thirds came from fertilized embryos representing eight developmental stages, but one third of all samples were removed as they were from unfertilized eggs. Between 10 to 30 samples per stage were used for further analyses.
The large number of samples for each timepoint were sufficient for sensitive pairwise Wilcoxon tests and correction for multiple testing between any two stages.
This statistical robustness would be reduced if fewer samples were used. This is especially important when looking at small changes in gene expression from genetically identical organisms.
How novel higher-throughput transcriptomics could help in similar studies:
Some novel sequencing technologies, such as BRB-seq, rely on adding a barcode to the 3’ end of mRNA molecules. This barcode allows the pooling of all samples so only one subsequent library preparation is required. This reduces both cost and technical variability between samples (Alpern et al., 2019), each of which were key considerations in this study.
For example, here the authors discarded one third of their data which would represent an enormous cost if traditional RNA-seq library preparations were used. The reduced cost of BRB-seq removes these expensive risks when working with sensitive samples and timepoints.
Furthermore, BRB-seq provides high quality data even with degraded mRNA (Alpern et al., 2019). mRNA degradation is a concern when working with low amounts of starting material. This could be critical in other developmental studies with low amounts of starting material or where material is extremely precious.
To find out more about how BRB-seq could help your study, please contact us at firstname.lastname@example.org
- Alpern, D., Gardeux, V., Russeil, J., Mangeat, B., Meireles-Filho, A.C., Breysse, R., Hacker, D. and Deplancke, B., 2019. BRB-seq: ultra-affordable high-throughput transcriptomics enabled by bulk RNA barcoding and sequencing. Genome biology, 20(1), pp.1-15.
- Barroso, G.V., Puzovic, N. and Dutheil, J.Y., 2018. The evolution of gene-specific transcriptional noise is driven by selection at the pathway level. Genetics, 208(1), pp.173-189.
- Eling, N., Morgan, M.D. and Marioni, J.C., 2019. Challenges in measuring and understanding biological noise. Nature Reviews Genetics, 20(9), pp.536-548.
- Irie, N. and Kuratani, S., 2011. Comparative transcriptome analysis reveals vertebrate phylotypic period during organogenesis. Nature communications, 2(1), pp.1-8.
- Kalinka, A.T., Varga, K.M., Gerrard, D.T., Preibisch, S., Corcoran, D.L., Jarrells, J., Ohler, U., Bergman, C.M. and Tomancak, P., 2010. Gene expression divergence recapitulates the developmental hourglass model. Nature, 468(7325), pp.811-814.
- Liu, J., Frochaux, M., Gardeux, V., Deplancke, B. and Robinson-Rechavi, M., 2020. Inter-embryo gene expression variability recapitulates the hourglass pattern of evo-devo. BMC biology, 18(1), pp.1-12.
- Raff, R.A., 2012. The shape of life: genes, development, and the evolution of animal form. University of Chicago Press.