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Updated: Apr 6, 2026

A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing

A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing

Published on: July 3, 2016

Deep Mutational Scanning: Library Construction, Functional Selection, and High-Throughput Sequencing.

Lea M Starita¹, Stanley Fields²

¹Department of Genome Sciences, University of Washington, Seattle, Washington 98195;

Cold Spring Harbor Protocols

|August 5, 2015

Summary

This summary is machine-generated.

Deep mutational scanning (DMS) uses high-throughput sequencing to analyze thousands of protein variants and their mutations. This method helps scientists understand how genetic changes impact protein function.

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Last Updated: Apr 6, 2026

A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing

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Published on: July 3, 2016

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Published on: July 15, 2018

Area of Science:

Biochemistry
Molecular Biology
Genomics

Background:

Deep mutational scanning (DMS) is a powerful technique for assessing protein function.
It enables the analysis of a vast number of protein variants simultaneously.
Understanding mutation effects is crucial for protein engineering and disease research.

Purpose of the Study:

To provide a comprehensive overview of the deep mutational scanning experimental workflow.
To detail the critical steps involved in library construction for protein variants.
To explain the process of preparing sequencing libraries for high-throughput platforms like Illumina.

Main Methods:

Deep mutational scanning involves creating large libraries of protein variants with diverse mutations.
High-throughput sequencing is employed to quantify the abundance of each variant before and after selection.
The experimental design focuses on robust library preparation for accurate downstream analysis.

Main Results:

The study outlines the key stages for conducting deep mutational scanning experiments.
It emphasizes the importance of meticulous library construction for reliable results.
Guidance is provided on preparing samples for Illumina sequencing.

Conclusions:

Deep mutational scanning is an effective method for mapping protein sequence-function landscapes.
The described protocols facilitate the application of DMS in various biological contexts.
This work serves as a practical guide for researchers utilizing high-throughput sequencing for functional genomics.