The effects of protein interactions, gene essentiality and regulatory regions on expression variation

BMC Systems Biology

Table 2 Analysis of four factors and their interactions affecting expression variation using stepwise selection with AIC.

variable	Ca_Na_exposure			Chemostat			Environmental Stress			Oxidative Stress
	model	p value	R²	model	p value	R²	model	p value	R²	model	p value	R²
x1	√	0.4252	0.05%	√	0.1582	0.16%	√	0.0647	0.28%	√	0.1075	0.21%
x2	√	0.3721	0.06%	√	0.0635	0.28%	√	0.0861	0.24%		0.8729	0.002%
x3	√	1.16E-20	6.76%	√	4.59E-09	2.73%	√	< 2e-16	13.42%	√	7.30E-09	2.65%
x4	√	3.22E-12	3.83%	√	7.96E-10	3.00%	√	< 2e-16	6.92%	√	0.8841	0.002%
x1*x2
x1*x3
x1*x4	√	0.0581	0.29%	√	0.0100	0.53%				√	0.0348	0.36%
x2*x3				√	0.0422	0.33%
x2*x4	√	0.0226	0.41%	√	0.0036	0.68%	√	0.0108	0.53%
x3*x4	√	0.0039	0.67%	√	0.0185	0.45%	√	6.2e-09	2.71%
R²model	16.36%			12.73%			22.39%			4.43%

The four main factors include protein interaction degree (x1), toxicity degree (x2: treat essential genes as ones with toxicity degree 4), number of TFs (x3), and the presence of TATA box (x4: 1-TATA containing genes, 0-non-TATA containing genes). The protein interaction data used in this analysis is based on the MIPS dataset. The column marked with "√" indicates inclusion in the final linear model. The multiple linear regression is based on the final linear model, respectively. The p-value is related to the null hypothesis that β ≠ 0 versus β = 0. R² is the variation explained by the model and each independent variable, respectively.

ISSN: 1752-0509