Gene duplication and the evolution of ribosomal protein gene regulation in yeast is a research paper published in Proceedings of the National Academy of Sciences (2010). On theSindex it has a DataRank of 2.6. It has been cited 74 times, with 62 citing works in its 1-hop citation network.
Coexpression of genes within a functional module can be conserved at great evolutionary distances, whereas the associated regulatory mechanisms can substantially diverge. For example, ribosomal protein (RP) genes are tightly coexpressed in Saccharomyces cerevisiae, but the cis and trans factors associated with them are surprisingly diverged across Ascomycota fungi. Little is known, however, about the functional impact of such changes on actual expression levels or about the selective pressures that affect them. Here, we address this question in the context of the evolution of the regulation of RP gene expression by using a comparative genomics approach together with cross-species functional assays. We show that an activator (Ifh1) and a repressor (Crf1) that control RP gene regulation in normal and stress conditions in S. cerevisiae are derived from the duplication and subsequent specialization of a single ancestral protein. We provide evidence that this regulatory innovation coincides with the duplication of RP genes in a whole-genome duplication (WGD) event and may have been important for tighter control of higher levels of RP transcripts. We find that subsequent loss of the derived repressor led to the loss of a stress-dependent repression of RPs in the fungal pathogen Candida glabrata. Our comparative computational and experimental approach shows how gene duplication can constrain and drive regulatory evolution and provides a general strategy for reconstructing the evolutionary trajectory of gene regulation across species.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.648
From this paper's citation signal
Citation Network Contribution
2.0
From 57 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 24% comes from its base citations and 76% from the citation network (57 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
Click a node to highlight its connections. Use scroll to zoom. Drag to pan.