To understand the relationship between transmembrane transport and tissue expression breadth on protein evolutionary rate, we split all the genes into three equally spaced bins according to their tissue expression breadth (bin 1: lower breadth [range: 1 7, n = 2,828], bin 2: medium breadth [range: 8 14, n = 1,444], and bin 3: higher breadth [range: 15 22, n = 2,783]).
For each gene, we then summed up the number of over expressed tissues to compute tissue expression breadth.
Two measures of tissue specificity were also calculated: probe detection and tissue expression breadth.
Although, we obtained a significant difference in tissue expression breadth within SHD, SPD, and ND genes, the above unexpected observation confirms that tissue expression breadth alone cannot explain the variation in evolutionary rates among genes of our interest.
Using equally populated bins (according to tissue expression breadth), a similar result was obtained (data not shown).
We interestingly obtained that network perturbations, tissue expression breadth, and gene functionality have substantial contributions to the evolutionary rate variations of SHD, SPD, and ND genes.
Peak expression was calculated as the maximum expression level across all tissues and expression breadth was the number of distinct tissues expressing the gene.
For each gene, the expression level was estimated as the average of 25 selected tissues, and expression breadth was measured as the number of tissues where it is expressed (expression level ≥ 200; see Su et al. 2002 ).
For each gene, expression level was computed as the median across the 79 tissues, and expression breadth was computed as the number of tissues in which the gene is expressed.
However, due to the limited gene detectability in poorly sampled tissues, the expression breadth of HK genes peaked at value 35 and diminished as breadth increased — most of HK genes can only be detected in 35 of 51 tissues.
