Dataset Information

Probing biophysical sequence constraints within the transmembrane domains of rhodopsin by deep mutational scanning.

ABSTRACT: Membrane proteins must balance the sequence constraints associated with folding and function against the hydrophobicity required for solvation within the bilayer. We recently found the expression and maturation of rhodopsin are limited by the hydrophobicity of its seventh transmembrane domain (TM7), which contains polar residues that are essential for function. On the basis of these observations, we hypothesized that rhodopsin's expression should be less tolerant of mutations in TM7 relative to those within hydrophobic TM domains. To test this hypothesis, we used deep mutational scanning to compare the effects of 808 missense mutations on the plasma membrane expression of rhodopsin in HEK293T cells. Our results confirm that a higher proportion of mutations within TM7 (37%) decrease rhodopsin's plasma membrane expression relative to those within a hydrophobic TM domain (TM2, 25%). These results in conjunction with an evolutionary analysis suggest solvation energetics likely restricts the evolutionary sequence space of polar TM domains.

SUBMITTER: Penn WD

PROVIDER: S-EPMC7056298 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Publications

Probing biophysical sequence constraints within the transmembrane domains of rhodopsin by deep mutational scanning.

Penn Wesley D WD McKee Andrew G AG Kuntz Charles P CP Woods Hope H Nash Veronica V Gruenhagen Timothy C TC Roushar Francis J FJ Chandak Mahesh M Hemmerich Chris C Rusch Douglas B DB Meiler Jens J Schlebach Jonathan P JP

Science advances 20200304 10

Membrane proteins must balance the sequence constraints associated with folding and function against the hydrophobicity required for solvation within the bilayer. We recently found the expression and maturation of rhodopsin are limited by the hydrophobicity of its seventh transmembrane domain (TM7), which contains polar residues that are essential for function. On the basis of these observations, we hypothesized that rhodopsin's expression should be less tolerant of mutations in TM7 relative to ...[more]

PMID: 32181350

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Project description:This dataset provides allele counts and raw fastqs for deep mutational scanning of the HIV-1 genes tat and rev when not-overlapped with one another (placed in the nef locus) as described in Fernandes et al. Functional segregation of overlapping genes in HIV Cell 2016 (in revision). Preselection (input) and post selection (replicate 1/2) files for every possible point mutant of these two HIV proteins from the NL4-3 background are given.Tab delimited files including codon counts across the amplicons are also included and are probably the most useful thing to most researchers. The data here was used to generate Figures 3 and 4 and 7 and might be of general use for people interested in deep mutational scanning, looking for signatures of epistasis in rev or tat, or reanalyzing and mining the data. FAQ: Why do the ends of each amplicon have such variation? In order to increase diversity across the flowcell, I pooled standard primers with N, NN, and NNN extensions to throw amplicons out of phase. When aligning you should trim the ends or ignore them. This means that the overlap between PE's can vary by 3 nt. Why are the filenames not easy to deal with? The filenames are tied to separate MiSeq runs. I hope to clean up the nomenclature and update this entry in the future while preserving the run information. You can get a sense of that as different residues will vary in Q-score, and that is mostly tied to the run they were pooled on and not any interesting biology. While this is makes it a little harder to follow, I think it's good to get a sense that doing this kind of analysis in high-throughput fashion leads to a reasonable amount of failure (i.e. RNA isolation, RT, fail) that led to repetition until we had good data for every position. Can you help me deal with this dataset? Yes. Please email me at jferna10@ucsc.edu, or contact me on twitter @jdf_ev. For reagents please contact Alan Frankel at frankel@cgl.ucsf.edu. Do you have the analysis scripts you used to process the data? Yes they are on github. https://github.com/nbstrauli/allele_frequency_trajectory_sim

Dataset Information

Probing biophysical sequence constraints within the transmembrane domains of rhodopsin by deep mutational scanning.

Publications

Probing biophysical sequence constraints within the transmembrane domains of rhodopsin by deep mutational scanning.

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