TY - JOUR
T1 - Drift barriers to quality control when genes are expressed at different levels
AU - Xiong, Kun
AU - McEntee, Jay P.
AU - Porfirio, David J.
AU - Masel, Joanna
N1 - Funding Information:
We thank Lilach Hadany, Yoav Ram, and other members of the Hadany group for helpful discussions that prompted us to explore variation in expression. We thank Paul Nelson for developing the idea of local error rates as an expansion of our model, Ben Wilson for help with R, and Etienne Rajon, Yoav Ram, Tobias Warnecke, and one anonymous reviewer, for helpful comments on the manuscript. We also thank Charles Traverse and Howard Ochman for sharing their data on transcriptional errors. An allocation of computer time from the University of Arizona Research Computing High Performance Computing (HPC) and High Throughput Computing (HTC) at the University of Arizona is gratefully acknowledged. This work was supported by the John Templeton Foundation [grant number 39667]. D.J.P. was also funded by the Undergraduate Biology Research Program at the University of Arizona(UA).
Publisher Copyright:
© 2017 by the Genetics Society of America.
PY - 2017/1
Y1 - 2017/1
N2 - Gene expression is imperfect, sometimes leading to toxic products. Solutions take two forms: globally reducing error rates, or ensuring that the consequences of erroneous expression are relatively harmless. The latter is optimal, but because it must evolve independently at so many loci, it is subject to a stringent “drift barrier”—a limit to how weak the effects of a deleterious mutation s can be, while still being effectively purged by selection, expressed in terms of the population size N of an idealized population such that purging requires s < -1/N. In previous work, only large populations evolved the optimal local solution, small populations instead evolved globally low error rates, and intermediate populations were bistable, with either solution possible. Here, we take into consideration the fact that the effectiveness of purging varies among loci, because of variation in gene expression level, and variation in the intrinsic vulnerabilities of different gene products to error. The previously found dichotomy between the two kinds of solution breaks down, replaced by a gradual transition as a function of population size. In the extreme case of a small enough population, selection fails to maintain even the global solution against deleterious mutations, explaining the nonmonotonic relationship between effective population size and transcriptional error rate that was recently observed in experiments on Escherichia coli, Caenorhabditis elegans, and Buchnera aphidicola.
AB - Gene expression is imperfect, sometimes leading to toxic products. Solutions take two forms: globally reducing error rates, or ensuring that the consequences of erroneous expression are relatively harmless. The latter is optimal, but because it must evolve independently at so many loci, it is subject to a stringent “drift barrier”—a limit to how weak the effects of a deleterious mutation s can be, while still being effectively purged by selection, expressed in terms of the population size N of an idealized population such that purging requires s < -1/N. In previous work, only large populations evolved the optimal local solution, small populations instead evolved globally low error rates, and intermediate populations were bistable, with either solution possible. Here, we take into consideration the fact that the effectiveness of purging varies among loci, because of variation in gene expression level, and variation in the intrinsic vulnerabilities of different gene products to error. The previously found dichotomy between the two kinds of solution breaks down, replaced by a gradual transition as a function of population size. In the extreme case of a small enough population, selection fails to maintain even the global solution against deleterious mutations, explaining the nonmonotonic relationship between effective population size and transcriptional error rate that was recently observed in experiments on Escherichia coli, Caenorhabditis elegans, and Buchnera aphidicola.
KW - Cryptic genetic variation
KW - Evolvability
KW - Proofreading
KW - Robustness
KW - Stop codon readthrough
KW - Transcriptional errors
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U2 - 10.1534/genetics.116.192567
DO - 10.1534/genetics.116.192567
M3 - Article
C2 - 27838629
AN - SCOPUS:85008449966
SN - 0016-6731
VL - 205
SP - 397
EP - 407
JO - Genetics
JF - Genetics
IS - 1
ER -