Divergent gene expression levels between diploid and autotetraploid Tolmiea relative to the total transcriptome, the cell, and biomass.

February 19th, 2019
By Gitzendanner, Matt

A simplified example of how spike‐in standards can be used during read normalization to enable comparisons of expression level at different biological scales between a hypothetical diploid–polyploid pair with differing cell density. The large circles represent a unit of biomass and contain a number of cells (green squares). Beneath each circle is a depiction of how the read normalizations are calculated. Under a per transcriptome normalization, the ratio of target transcripts to the total transcriptome is compared. The per biomass normalization uses the ratio of the transcript of interest to the spike‐in transcripts. The per cell normalization also uses the ratio of the transcript of interest to spike‐in transcripts, but scales the spike‐in transcript abundance by cell density, represented here by multiplying the spike‐in abundance by the number of contributing cells. Whether the transcript of interest would be found as not differentially expressed (=) or upregulated (<) in the polyploid under each normalization is indicated (downregulated not included). DE: differential expression.

Visger, C. J., G. K.-S. Wong, Y. Zhang, P. S. Soltis, and D. E. Soltis. 2019. Divergent gene expression levels between diploid and autotetraploid Tolmiea relative to the total transcriptome, the cell, and biomass. American Journal of Botany [View on publisher’s site]

Abstract

Premise of the Study

Studies of gene expression and polyploidy are typically restricted to characterizing differences in transcript concentration. Using diploid and autotetraploid Tolmiea, we present an integrated approach for cross‐ploidy comparisons that account for differences in transcriptome size and cell density and make multiple comparisons of transcript abundance.

Methods

We use RNA spike‐in standards in concert with cell size and density to identify and correct for differences in transcriptome size and compare levels of gene expression across multiple scales: per transcriptome, per cell, and per biomass.

Key Results

In total, ~17% of all loci were identified as differentially expressed (DEGs) between the diploid and autopolyploid species. The per‐transcriptome normalization, the method researchers typically use, captured the fewest DEGs (58% of total DEGs) and failed to detect any DEGs not found by the alternative normalizations. When transcript abundance was normalized per biomass and per cell, ~66% and ~82% of the total DEGs were recovered, respectively. The discrepancy between per‐transcriptome and per‐cell recovery of DEGs occurs because per‐transcriptome normalizations are concentration‐based and therefore blind to differences in transcriptome size.

Conclusions

While each normalization enables valid comparisons at biologically relevant scales, a holistic comparison of multiple normalizations provides additional explanatory power not available from any single approach. Notably, autotetraploid loci tend to conserve diploid‐like transcript abundance per biomass through increased gene expression per cell, and these loci are enriched for photosynthesis‐related functions.

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