In one of the largest studies of its kind, researchers used bulk RNA-seq to decode the gene expression landscape of development. The study focused on seven organs from seven different species, before and after birth (Cardoso-Moreira et al., 2019).
Cardoso-Moreira et al. found that gene expression networks were often similar in all organs and species in their data set, although some were species and organ specific.
Many of these similar networks were involved in key developmental processes. This suggests that fundamental transcriptional networks originated early in mammalian evolution, more than 200 million years ago.
In this article we explore how RNA-seq was fundamental to these findings and how novel sequencing technologies could help similar studies in the future.
Summary:
In the pre-genomics era, knowledge of gene expression dynamics in mammals was limited to individual genes, specific organs, or phases in development (Guttmacher and Collins 2003).
Data generated by Cardoso-Moreira et al. provides an unprecedented resource to tease apart developmental gene expression networks of multiple organs and species on a genome wide scale.
The study includes 1,893 bulk RNA-seq samples covering the development of brain, cerebellum, heart, kidney, ovary, testis, and liver. Samples are from both before and after birth. Data was generated for human, rhesus macaque, mouse, rat, rabbit, opossum, and chicken (Table 1).
Species |
Number of samples |
Human |
297 |
Macaque |
168 |
Mouse |
316 |
Rat |
350 |
Rabbit |
315 |
Opossum |
232 |
Chicken |
215 |
Total |
1,893 |
Table 1 – Number of samples sequenced per species
Comparative analyses of gene expression dynamics in each organ and species found that different mammalian species have similar gene expression patterns, despite diverging from each other millions of years ago.
This suggests that many of the transcriptional networks involved in key developmental processes must have originated early on in mammalian evolution.
Conversely, some gene expression patterns through development were unique to one organ from a specific species.
This led to the hypothesis that such genes may determine species-specific organ characteristics such as brain development in humans.
How RNA-seq was used:
Firstly, 1,893 bulk RNA-seq libraries were generated for seven species using the TruSeq Stranded mRNA LT Sample Prep Kit from Illumina (Table 1). They were sequenced with an Illumina HiSeq 2000 for 100 nucleotides single-end reads with a median depth of 33 million reads per sample.
Next, the researchers quantified gene expression changes across all organs in each species, and searched for similarities and differences between early and later development. The authors identified that most genes changed expression throughout development within an individual organ.
Specialized time-course algorithms then allowed alignment of corresponding stages in different species (Hensman, Lawrence & Rattray 2013). This was followed by a comparative analysis of gene expression trajectories between species for all organs.
How the large number of samples contributed to the results:
RNA-seq was performed on between 168 to 350 samples per species (Table 1). For each species, seven organs were sequenced before and after birth, with a median of two to three replicates per stage for each organ and species.
Sufficient statistical power was obtained for most analyses thanks to the large sample size. It allowed novel analyses that covered the whole range of development to be performed in a statistically robust manner.
Additionally, it enabled the direct comparison of gene expression in organ development within, but also across mammals.
Furthermore, the authors ensured that more than one replicate was present for each stage. This was key to having enough statistical power to detect robust changes at particular stages, especially when determining cross-species comparisons.
How novel higher-throughput transcriptomics could help in similar studies:
Although the overall number of samples per species was impressive, individual stages had relatively few samples. This reduced the statistical power to detect smaller expression changes at specific time points. Future studies on mammalian development would benefit from higher sample size per stage.
In such large-scale studies cost may be a limiting factor. New 3’ mRNA-seq methods such as Bulk RNA Barcoding and sequencing (BRB-seq) can significantly reduce this expense.
This technology is reliant on the barcoding of mRNA and subsequent multiplexing of samples to allow the sequencing of hundreds of samples in the same run.
The larger sample numbers enabled by BRB-seq would provide an unprecedented resolution for future time course studies.
To find out more about how BRB-seq could help your large-scale RNA-seq study, please contact us at info@alitheagenomics.com.
References:
Cardoso-Moreira, M., Halbert, J., Valloton, D., Velten, B., Chen, C., Shao, Y., Liechti, A., Ascenção, K., Rummel, C., Ovchinnikova, S. and Mazin, P.V., 2019. Gene expression across mammalian organ development. Nature, 571(7766), pp.505-509.
Guttmacher, A.E. and Collins, F.S., 2003. Welcome to the genomic era. New England Journal of Medicine, 349(10), pp.996-998.
Hensman, J., Lawrence, N.D. and Rattray, M., 2013. Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters. BMC bioinformatics, 14(1), pp.1-12.