fairfolio
Saved Projects

What's So Great about Sex?

CSEF · 2006 Mathematics & Software

Justin Feng, Alexander Kayfetz-Gaum · San Marcos Senior High School, Santa Barbara

Overview

Objectives/Goals To determine whether the rate of evolution towards on optimal genome is greater among a sexually reproducing population (SRP) or an asexually reproducing population (ARP). Methods/Materials Construct two separate computer programs using the programming language Python. One simulates evolution among a SRP and the other simulates evolution among an ARP. Each individual strives to become more fit, which is defined as the distance between an individual's genome and the target and reach a target genome. Adjusting certain values, such as genome size, average mutation rate, etc., makes it possible to compare average evolutionary efficiency under different conditions to acquire the most accurate results possible. Results The sexually reproducing population achieved a higher level of fitness at a faster rate than the asexually reproducing population. Changing the values of the parameters created both favorable conditions and extreme conditions in which the populations were to evolve, and only when the average mutation size was extremely high was asexual reproduction advantageous in the evolutionary process. Conclusions/Discussion The results we acquired are further proof of why more species in real-life reproduce sexually rather than asexually. We surmise that genetic recombination and variability account for the superiority of sexual reproduction. Because an offspring's genome in a SRP takes beneficial genes from two parents, it will become more fit at a faster rate while also increasing genetic variability within the entire gene pool. Because of the close similarity between a parent and an offspring's genomes in an ARP, genetic variability is low and the population as a whole does not evolve at as fast of a rate as the SRP.

Summary statement

This project explores whether sexual reproduction or asexual reproduction is more efficient in the evolutionary process of a population.

Help received

Stefan Karpinski helped with improving and looking over the programs.

Competition history

  • CSEF 2006 Mathematics & Software · Entry S1206

Resources

Related projects

Closest projects by meaning, across every fair and year in the corpus.

Browse more like this

Source: California Science & Engineering Fair public projects

Save projects to your library

Sign in with Google to keep track of projects you find interesting, organized into folders. An account also raises your daily allowance for “Has this been done?”, and lets you create a key for the MCP server with a much higher limit than anonymous use. Browsing stays public.

Continue with Google