Abstract
Protein Protein low complexity regions (LCRs) are compositionally biased amino acid sequences, many of which have significant evolutionary impacts on the proteins which contain them. They are mutationally unstable experiencing higher rates of indels and substitutions than higher complexity regions. LCRs also impact the expression of their proteins, likely through multiple effects along the path from gene transcription, through translation, and eventual protein degradation. It has been observed that proteins which contain LCRs are associated with elevated transcript abundance (TAb), despite having lower protein abundance. We have gathered and integrated human data to investigate the co-evolution of TAb and LCRs through ancestral reconstructions and model inference using an approximate Bayesian calculation based method. We observe that on short evolutionary timescales TAb evolution is significantly impacted by changes in LCR length, with insertions driving TAb down. But in contrast, the observed data is best explained by indel rates in LCRs which are unaffected by shifts in TAb. Our work demonstrates a coupling between LCR and TAb evolution, and the utility of incorporating multiple responses into evolutionary analyses.
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Code Availability
Custom Perl and R scripts used for quality control of input data and reconstruction of ancestral TAb and LCR states can be found on Github at: www.github.com/zacherydickson/AncRecon-LCR-TAb. The program written to perform ABC inference of co-evolutionary models can be found on Github at: www.github.com/zacherydickson/ABC-LCR-TAb
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This work was funded by the Natural Sciences and Engineering Research Council of Canada (grants RGPIN-202-05733 to GBG and PGSD3-547476-2020 to ZWD).
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Dickson, Z.W., Golding, G.B. Evolution of Transcript Abundance is Influenced by Indels in Protein Low Complexity Regions. J Mol Evol 92, 153–168 (2024). https://doi.org/10.1007/s00239-024-10158-z
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DOI: https://doi.org/10.1007/s00239-024-10158-z