4.3 Article

Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays

Journal

JOURNAL OF MOLECULAR EVOLUTION
Volume 91, Issue 3, Pages 334-344

Publisher

SPRINGER
DOI: 10.1007/s00239-023-10098-0

Keywords

Barcode; Fitness; Pooled growth; High-throughput phenotyping

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The fitness of a genotype is determined by its reproductive success, which is influenced by multiple underlying phenotypes. Measuring fitness is crucial for understanding how changes in cellular components affect a cell's ability to reproduce. This study presents an improved Python-based method for estimating fitness using pooled competition assays.
The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell's ability to reproduce. Here, we describe an improved approach, implemented in Python, for estimating fitness in high throughput via pooled competition assays.

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