| Literature DB >> 32853297 |
Jeremy W Schroeder1, T Sabari Sankar2, Jue D Wang1, Lyle A Simmons3.
Abstract
Replication-transcription conflicts promote mutagenesis and give rise to evolutionary signatures, with fundamental importance to genome stability ranging from bacteria to metastatic cancer cells. This review focuses on the interplay between replication-transcription conflicts and the evolution of gene directionality. In most bacteria, the majority of genes are encoded on the leading strand of replication such that their transcription is co-directional with the direction of DNA replication fork movement. This gene strand bias arises primarily due to negative selection against deleterious consequences of head-on replication-transcription conflict. However, many genes remain head-on. Can head-on orientation provide some benefit? We combine insights from both mechanistic and evolutionary studies, review published work, and analyze gene expression data to evaluate an emerging model that head-on genes are temporal targets for adaptive mutagenesis during stress. We highlight the alternative explanation that genes in the head-on orientation may simply be the result of genomic inversions and relaxed selection acting on nonessential genes. We seek to clarify how the mechanisms of replication-transcription conflict, in concert with other mutagenic mechanisms, balanced by natural selection, have shaped bacterial genome evolution.Entities:
Mesh:
Year: 2020 PMID: 32853297 PMCID: PMC7451550 DOI: 10.1371/journal.pgen.1008987
Source DB: PubMed Journal: PLoS Genet ISSN: 1553-7390 Impact factor: 5.917
Fig 1Genome-wide bias against head-on genes reflects negative selection.
(A) The B. subtilis genome is represented to scale as a circle filled with blue or orange to represent loci of the genome containing co-directional and head-on genes, respectively. The origin (oriC) and terminus (terC) of replication are labelled. Strain PY79 is shown but the basic genome organization is conserved among B. subtilis strains. (B) Schematic of random inversions of genomic loci and evolutionary outcomes depending on selection. In the absence of selection against head-on genes, genomic inversions over time would eventually result in a 50:50 distribution of head-on:co-directional genes. In the presence of selection against head-on genes, gene content is biased in favor of co-directional genes. Genes that remain head-on are typically those for which there is less selection against the head-on orientation.
Most stress-induced genes are co-directional.
| Stress-associated regulator | Number of head-on CDSs in regulon | Number of co-directional CDSs in regulon | |||
|---|---|---|---|---|---|
| LexA | 14 | (1.2%) | 46 | (1.5%) | 0.59 |
| SigB | 72 | (6.1%) | 149 | (4.7%) | 0.078 |
| SigM | 23 | (2.0%) | 70 | (2.2%) | 0.67 |
| SigV | 14 | (1.2%) | 7 | (0.22%) | 0.00013 |
| SigX | 9 | (0.07%) | 33 | (1.0%) | 0.50 |
| SigY | 0 | (0%) | 7 | (0.22%) | 0.23 |
| SinR | 13 | (1.1%) | 36 | (1.1%) | 0.96 |
| Spo0A | 25 | (2.1%) | 117 | (3.7%) | 0.012 |
| Spx | 3 | (0.25%) | 38 | (1.2%) | 0.0069 |
*Only CDSs activated by Spx are included.
The number of head-on and co-directional CDSs in B. subtilis strain 168 regulated by each transcription factor was tabulated. In addition, their percentage over the total number of head-on or co-directional CDSs is in parentheses.
Abbreviations: CDS, coding sequence; LexA, repressor of the SOS response to DNA damage; SigB, general stress response; SigM, cell envelope stress response; SigV, cell envelope stress response; SigX, cell envelope stress response; SigY, cell envelope stress response; SinR, biofilm; Spo0A, sporulation; Spx, oxidative stress
Fig 2Head-on and co-directional genes have similar expression properties.
Distributions of two metrics relating to gene expression in B. subtilis transcriptomic datasets. Distributions were subset by direction of transcription relative to DNA replication. Vertical lines represent the mean for each class of genes. (A) The distribution of gene expression values for CDSs in B. subtilis strain PY79. The z-score was calculated for each CDS’s natural-logarithm-transformed RPKM values prior to subsetting by direction. RNA-seq data are from [22]. (B) Transcriptomic microarray data [53] were analyzed. Each gene’s Gini coefficient was calculated over 104 conditions. CDS, coding sequence; RPKM, reads per kilobase per million reads mapped