Challenge Team Interim Report


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    Team Number: 011

    School Name: Bernalillo High School

    Area of Science: Biology

    Project Title: DNA Diversity

Abstract
Interim
Final Report

Background Information

Scientists today have learned how to read the DNA strand; they find many errors. What causes these errors to show up in our genes? Most of these errors are harmless. Chromosomes duplicate each time a cell divides and generally there are going to be some mistakes in this process. We inherit many genetic mutations from our parents. DNA in our cells go through 30 new mutations during our lifetime. Either through mistakes during DNA copying, or cell division, or more often because of damage from the environment. Bits of our DNA may be deleted, inserted, broken, or substituted. Problems arise only when an error in DNA alters a message that tells certain cells to manufacture a certain protein. Much of the recent progress in reading DNA has come from the analysis of genetic errors.

Project Definition

We are going to manipulate the data on a supercomputer to predict the size of a population needed to ensure genetic diversity.

Proposed Method of Solution

Start off with a population of individuals containing all these genes. Simulate reproduction, with half of the genes coming from each parent. Every few hundred generations, throw in a disaster that only one (dominant) gene can save an individual from. Some of the disaster-averting genes may be recessives, which would mean it would take 2 of them to save the creature from the disaster. Now, if the population is small, some of these genes may get lost entirely after a few generations. If the genes are not present to defend against a disaster, the entire population might die. By simulating many generations and disasters over time, you could determine how large a population needs to be or avert catastrophe through genetic loss. Remember, a disaster reduces the population and genetic diversity, so you need to have a larger size so that genes can survive catastrophe.

Expected Results

For all of our team members to gain knowledge of DNA and Genetics, also how supercomputers run programs through a lot of data. This will further our knowledge in computer skills and problem solving.

Progress to Date



Team Members

Sponsoring Teachers

Project Advisor(s)