I am building statistical models to analyse output from Illumina shotgun sequencing (HiSeq 4000) on stool samples (but RNA-seq data should behave similarily). The raw counts are a statistical sample of the total collection of DNA molecules used as input for the sequencing machine, and I think we can assume that the sequencing platform has limited capacity, such that detected reads are always a small fraction of the the original sequencing library.
Consider two different samples: one control sample and one treatment sample, which is identical apart from a single species (or gene) that has much higher absolute abundance relative what it in the control. As a result, the reads of this species will be much higher in the treatment sample, and also the 'real estate' of the remaining genes in that sample will be decreased. This is simply the nature of relative abundances.
However, size factor estimation that uses the "median ratio method" (http://dx.doi.org/10.1186/gb-2010-11-10-r106) for instance, are based on "experience with real data [...] [that] shows [that] a few highly and differentially expressed genes [or abundant species] may have strong influence on the total read count." (http://dx.doi.org/10.1186/gb-2010-11-10-r106). I am curious to see experimental evidence for this last statement. Or does someone have at least an explanation of how total read count can be affected by the absolute abundance of a species/gene?