Genotype to Phenotype Mapping and the Fitness Landscape of the E. coli lac Promoter

• Type of Material: Article
• Authors: Jakub Otwinowski, Emory University; Ilya Nemenman, Emory University
• Language: English
• Date: 2013-05-01
• Publisher: Public Library of Science
• Publication Version: Final Published Version
• Copyright Statement: © 2013 Otwinowski, Nemenman. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0061570
• Title of Journal or Parent Work: PLoS ONE
• ISSN: 1932-6203
• Volume: 8
• Issue: 5
• Start Page: 1
• End Page: 10
• Grant/Funding Information: The work has been funded, in part, by the HFSP program and the James S. McDonnell Foundation.
• Research Categories: Biology, Genetics; Physics, General

Abstract

Genotype-to-phenotype maps and the related fitness landscapes that include epistatic interactions are difficult to measure because of their high dimensional structure. Here we construct such a map using the recently collected corpora of high-throughput sequence data from the 75 base pairs long mutagenized E. coli lac promoter region, where each sequence is associated with its phenotype, the induced transcriptional activity measured by a fluorescent reporter. We find that the additive (non-epistatic) contributions of individual mutations account for about two-thirds of the explainable phenotype variance, while pairwise epistasis explains about 7% of the variance for the full mutagenized sequence and about 15% for the subsequence associated with protein binding sites. Surprisingly, there is no evidence for third order epistatic contributions, and our inferred fitness landscape is essentially single peaked, with a small amount of antagonistic epistasis. There is a significant selective pressure on the wild type, which we deduce to be multi-objective optimal for gene expression in environments with different nutrient sources. We identify transcription factor (CRP) and RNA polymerase binding sites in the promotor region and their interactions without difficult optimization steps. In particular, we observe evidence for previously unexplored genetic regulatory mechanisms, possibly kinetic in nature. We conclude with a cautionary note that inferred properties of fitness landscapes may be severely influenced by biases in the sequence data.