Spatial and Temporal Control of Evolution through Replication-Transcription Conflicts

Abstract

Evolution could potentially be accelerated if an organism could selectively increase the mutation rate of specific genes that are actively under positive selection. Recently, a mechanism that cells can use to target rapid evolution to specific genes was discovered. This mechanism is driven by gene orientation-dependent encounters between DNA replication and transcription machineries. These encounters increase mutagenesis in lagging-strand genes, where replication-transcription conflicts are severe. Due to the orientation and transcription-dependent nature of this process, conflict-driven mutagenesis can be used by cells to spatially (gene-specifically) and temporally (only upon transcription induction) regulate the rate of gene evolution. Here, I summarize recent findings on this topic, and discuss the implications of increasing mutagenesis rates and accelerating evolution through active mechanisms.

Keywords: Evolution; Evolution of evolvability; Genome organization; Lagging-strand genes; Mutagenesis; Replication–transcription conflicts; TC-NER.

Figure 1. Cartoon depiction of the two types of replication-transcription conflicts

The replisome is represented by the purple sphere and RNA polymerase is represented by the blue-green sphere. Newly synthesized strands of the DNA are black. The mRNA is dark gray. Cartoon represents conflicts occurring at a gene that is encoded on the lagging strand (head-on) or leading strand (co-directional).

Figure 2. Gene orientation bias across various bacterial species

The fraction of genes encoded on the leading strand are shaded in lavender, and the fraction encoded on the lagging strand are shaded in darker purple. Abbreviations (Percent of genes encoded on the leading strand): Top row: Mg, Mycoplasma genitalium G37 (80.8%); Sp, Streptococcus pneumoniae TIGR4 (80.3%); Sa, Staphylococcus aureus NCTC 8325 (76.8%); Ss, Streptococcus sanguinis SK36 (75.3%); Sa, Staphylococcus aureus N315 (74.8%); Bs, Bacillus subtilis 168 (73.8%); Ab, Acinitobacter ADP1 (60.7%). Middle row: Bt, Burkholderia thailandensis E264 (59.3%); Mt, Mycobacterium tuberculosis H37Rv (59.0%); St, Salmonella enterica serovar Typhimurium LT2 (58.6%); Sty, Salmonella enterica serovar Typi Ty2 (58.1%); Btm, Bacteroides thetaiotaomicron VPI-5482 (58.0%); Hp, Helicobacter pylori 26695 (57.8%); St, Salmonella enterica serovar Typhimurium 14028S (57.3%). Bottom row: Pa, Pseudomonas aeruginosa PA01 (55.9%); So, Shewanella oneidensis MR-1 (55.7%); Hi, Haemophilus influenzae Rd KW20 (55.0%); Ec, Escherichia coli K-12 MG1655 (54.9%); Cc, Caulobacter crescentus NA1000 (54.7%); Pa, Pseudomonas aeruginosa UCBPP-PA14 (54.1%); Pg, Porphyromonas gingivalis ATCC 33277 (51.4%). Data were extracted and compiled from analyses presented in [60].