| Methods | Archived Data |
Overview of the Cow Diversity Project
The aims of the Cow Diversity Project are:
- to provide students with experience in a variety of molecular genetic
methods, including DNA extraction/purification, restriction digestion, PCR, gel
electrophoresis and cycle-sequencing;
- to provide students with a glimpse into the nature of molecular genetic variation;
and
- to help students appreciate the link between genetics and evolution.
We encourage others to join in the Project. We will add any high-quality (double-stranded) DNA sequences to the archived data set, with the one requirement that the the data be collected in an undergraduate laboratory course.
The mitochondrial D-loop and ND3 loci have been chosen for a few reasons.
- First, mitochondrial loci are effectively monoploid, so heterozygosity should be
rare (arising only from heteroplasmy). Thus, direct sequencing of purified PCR products
is straightforward. The entire laboratory exercise, from DNA extraction through
cycle-sequencing, can be accomplished in five (or fewer) 3-hour laboratory
sessions.
- Second, mitochondrial genomes are present in high copy number per cell; PCR should
still work if the DNA is moderately degraded. Students do not need to take special
care of their samples -- storage at room temperature in rubbing alcohol works fine.
- Third, PCR for both loci is robust. Primers have been designed against conserved regions, and PCR has worked with every successful DNA prep to date. Furthermore, unlike most nuclear loci, the ND3 gene is short (encoding a 115-amino acid polypeptide), uninterrupted by introns, and very close to flanking protein-coding genes. It can be bidirectionally sequenced in its entirety (start through stop codon) using dilutions of the two PCR primers.
The Cow Diversity Project is not intended to produce data for publication in peer-reviewed primary research journals, and we discourage anyone from using the data for research purposes. The provenance of supermarket beef is unknown to the purchaser, and population genetic analysis of the data will likely be based on nonrandom samples.
