Results: 5

1.
Figure 4

Figure 4. Targets of fast evolving TFs have larger expression changes through evolution.. From: Regulatory Network Structure as a Dominant Determinant of Transcription Factor Evolutionary Rate.

The targets of the 25% fastest evolving TFs, on the right, have on average larger absolute fold changes in expression between S. cerevisiae and S. paradoxus than targets of other TFs, on the left, as determined by RNA-seq. Numbers above the bars represent the number of TFs in the bin.

Jasmin Coulombe-Huntington, et al. PLoS Comput Biol. 2012 October;8(10):e1002734.
2.
Figure 2

Figure 2. TFs and their targets co-evolve as modules.. From: Regulatory Network Structure as a Dominant Determinant of Transcription Factor Evolutionary Rate.

Each data point is based on a TF with 3 or more targets. (A) TF Ka/Ks as a function of the median Ka/Ks of target genes. (B) TF Ka/Ks as a function of the fraction of target genes missing an ortholog in S. paradoxus (lost in S. paradoxus or gained in S. cerevisiae). Numbers above the bars represent the number of TFs in the bin.

Jasmin Coulombe-Huntington, et al. PLoS Comput Biol. 2012 October;8(10):e1002734.
3.
Figure 1

Figure 1. Distinct evolutionary trends of TFs.. From: Regulatory Network Structure as a Dominant Determinant of Transcription Factor Evolutionary Rate.

Unlike average proteins, TF Ka/Ks correlates positively with regulatory in-degree and very poorly with CAI and the evolutionary rate of PPI network neighbors. Ka/Ks is displayed as a function of regulatory in-degree (A–B), CAI (C–D) and median Ka/Ks of interacting proteins (E–F) for all proteins (A,C,E) and TFs (B,D,F). Numbers above the bars represent the number of TFs/proteins in the bin.

Jasmin Coulombe-Huntington, et al. PLoS Comput Biol. 2012 October;8(10):e1002734.
4.
Figure 3

Figure 3. Comparison of different genomic and network features influencing TF and protein evolutionary rate.. From: Regulatory Network Structure as a Dominant Determinant of Transcription Factor Evolutionary Rate.

For each determinant, absolute Spearman's rank correlation coefficient (ρ) for TFs is displayed on the left and for all proteins, on the right, with the color of the box representing the direction of the trend. The * indicates the most dominant correlation for each protein set. While CAI is the dominant correlate with Ka/Ks for generic proteins, target gene Ka/Ks is the strongest correlate for TF Ka/Ks.

Jasmin Coulombe-Huntington, et al. PLoS Comput Biol. 2012 October;8(10):e1002734.
5.
Figure 5

Figure 5. TFs co-evolve with activated targets, but not with repressed targets.. From: Regulatory Network Structure as a Dominant Determinant of Transcription Factor Evolutionary Rate.

Edge signs are inferred from TF knock-out expression data. Each data point is based on a TF with 5 or more targets regulated in the same direction. (A) Median Ka/Ks of activated target genes as a function of TF Ka/Ks. (B) Median Ka/Ks of repressed target genes as a function of TF Ka/Ks. (C) Fraction of activated targets missing an ortholog in S. paradoxus as a function of TF Ka/Ks. (D) Fraction of repressed targets missing an ortholog in S. paradoxus as a function of TF Ka/Ks. Numbers above the bars represent the number of TFs in the bin.

Jasmin Coulombe-Huntington, et al. PLoS Comput Biol. 2012 October;8(10):e1002734.

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