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Amylase Copy Number and Diet

By Rebecca Orr1, Ruth Buskirk2, Kristin Harvey2

1. Collin College 2. University of Texas at Austin

An adapted module from HHMI Spreadsheet Tutorials using amylase data for students to gain data analysis and excel skills

Listed in Teaching Materials | resource by group HHMI BioInteractive

Version 1.0.0 - published on 18 Jan 2018 doi:10.25334/Q4H10B - cite this Last public release: 2.0.0

Licensed under CC Attribution-NonCommercial-NoDerivatives 4.0 International according to these terms

Adapted from: Spreadsheet Data Analysis Tutorial Series v 1.0



General biology students learn about hydrolysis reactions, role of starch, enzymes, and genes when studying macromolecules. They do not, however, often make connections between the enzymes responsible for hydrolysis and the genes responsible for the production of hydrolytic enzymes. Furthermore, students tend not to appreciate the impact of specific environments on the presence and/or copy number of specific nucleic acids and proteins. This module seeks help students to make these connections while addressing two distinct learning goals, one that is content-based and one that is develops quantitative competency in freshman biology students.


Learning Goals for "Amylase Copy Number and Diet;

  1. To understand amylase enzyme function and the role the amylase gene copy number might play in conferring a selective advantage for an organism in high-starch and low-starch environments.
  2. To develop students' science process skills by teaching students how to utilize descriptive statistics such as mean, median, and standard deviation and how to evaluate histograms.


Cite this work

Researchers should cite this work as follows:



Data from Perry, G.H., Dominy, N.J., Claw, K.G., Lee, A.S., Fiegler, H., Redon, R., Werner, J., Villanea, F.A., Mountain, J.L., Misra, R. and Carter, N.P., 2007. Diet and the evolution of human amylase gene copy number variation. Nature genetics39(10), pp.1256-1260.

A random number generator in EXCEL was used to select the subsamples from the larger data set that was available in the supplement of the Perry et al. (2007) paper.

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