Explain what a GWAS is. How are SNPs used in this process?

In this activity, students explore single nucleotide polymorphisms (SNPs) that are associated with different traits
in dogs to help identify genes associated with those traits. The activity is based on actual genome-wide
association studies (GWAS) with dogs. First, students learn about GWAS and SNPs, then answer questions about
a news release that describes a real GWAS. Students then engage with a hands-on card activity to identify
associations between certain phenotypes and SNPs in dogs. The activity includes an optional extension in which
students use chi-square analysis to determine whether the associations are statistically significant.
This activity complements the 2013 Holiday Lecture “Dog Genomics and Dogs as Model Organisms,” in which
biologist Elinor Karlsson discusses how dogs can be used as model organisms for genomic studies, such as
GWAS. The activity includes actual sequence data from DNA isolated from dog saliva, which was obtained and
analyzed by Karlsson and her colleagues.
Additional information related to pedagogy and implementation can be found on this resource’s webpage,
including suggested audience, estimated time, and curriculum connections.
KEY CONCEPTS
• Comparing DNA sequences of many individuals reveals common variations across the genome.
• Some DNA variations occur more frequently in individuals with one form of a trait than another.
• Variations associated with a trait can point to the location of the gene (or genes) responsible for that trait.
• DNA sequences closer together on a chromosome tend to get inherited together and will often stay
together over evolutionary time.
STUDENT LEARNING TARGETS
• Describe how a genome-wide association study (GWAS) works and what questions it can be used to
investigate.
• Explain how GWAS uses single nucleotide polymorphisms (SNPs) to identify genes that affect a trait of
interest.
• Identify and interpret patterns in real genomic data.
PRIOR KNOWLEDGE
Students should be familiar with:
• the concept of genes and mutations
• the relationship between genotype and phenotype
• the relationship between a single gene, a chromosome, and the genome
• the difference between coding and regulatory regions in the genome
MATERIALS
• copies of the “Student Handout”
• both sets of “SNP Cards” (curly-straight, short-long)
• (optional) access to the video lecture “Dog Genomics and Dogs as Model Organisms”
TEACHING TIPS
Running the Activity
• Students can work individually or in groups.
• Time estimates for each part of the “Student Handout” are as follows:
o Part 1 may take about 30 to 40 minutes to complete, depending on the student’s reading ability. Parts
2–5 may take about 20 minutes of in-class time, depending on the amount of collaboration. You may
need additional time for answering questions and class discussion.
o The “Extension” section may take another 20 minutes, depending on students’ backgrounds.
• After Part 1, you may want to discuss the readings in class and address student questions or points of
confusion. Suggested discussion questions include:
o What is the relationship between a complete genome, a chromosome, and a gene?
o How are SNPs used in a GWAS?
o How can GWAS be used to find genes that cause disease?
o What is the difference between a SNP and a mutation?
• For Parts 3 and 4, you will need to print complete sets of “SNP Cards” for each student or group. You could
laminate the cards for repeat use.
o Use the coat length cards (“short-long”) for Part 3. These cards show SNP alleles at seven loci on
chromosome 32 in 12 dogs with either short or long coats.
o Use the coat texture cards (“straight-curly”) for Part 4. These cards show SNP alleles at six loci on
chromosome 27 in 10 dogs with either straight or curly coats.
• The “Extension” section is optional and is most useful for students with some background in chi-square
analysis. It can be used to practice statistical methods.
Clarifications and Caveats
• The “Student Handout” uses the term “allele” to refer to variations of SNPs, which may also be called
“genetic variants” or “SNP variants.” Some scientists use the term “allele” to refer only to variations that
cause changes in phenotypes, which is not always the case for variations in SNPs.
• The conceptual framework of GWAS relies on the concept of genetic linkage, which is typically taught during
Mendelian genetics. This activity does not explore genetic linkage in depth.
o If students are not familiar with genetic linkage, you may want to briefly summarize the following points
so that they will understand the principles behind GWAS better:
▪ Two DNA sequences on the same chromosome are said to be “linked” if they tend to be inherited
together during meiosis.
▪ If meiotic crossing-over occurs between the two sequences, they will not be inherited together.
▪ The chance of crossing-over occurring between the two sequences depends on the physical distance
between them. If they are closer together, the chance is smaller.
▪ Therefore, two sequences on the same chromosome that are close together tend to be inherited
together more often than those that are far apart.
▪ Over evolutionary time, two sequences that are closer together tend to stay together.
o You could take the opportunity to discuss genetic linkage when describing the difference between a SNP
that causes a trait (causative SNP) and an associated SNP that does not cause a trait. Even if a SNP shows
strong association with a trait in GWAS, it takes further investigation to see if it is a causative SNP (i.e., in
the noncoding or coding region of the gene) or if it’s simply closely linked to the causative part of the
genome.
• Although this activity shows only a few SNPs on two chromosomes, a real GWAS uses millions of SNPs across
the entire genome. A computer then sifts through the data to find associations. This activity uses simple
examples that can be done without a computer to demonstrate the concepts involved.
• Although the human genome was obtained by pooling sequence data from several individuals,
the referencedog genome consists of data from just one dog (Tasha). Scientists have also
sequenced dogs from other breeds and put all the differences they found compared to Tasha’s
genome in the public database dbSNP.
Supplements and Extensions
• The optional video lecture “Dog Genomics and Dogs as Model Organisms,” which provides an
introductionto GWAS in dogs, is useful for enhancing the activity.
o Chapters 2–6 (time 1:56 to 12:15) are the segments of the video most relevant to the
activity. In particular, starting around 10:15, the video shows how to analyze SNP data
similar to those in Parts 2–4of the activity. Consider having students watch these segments
as homework or in class.
o In this video, Dr. Karlsson uses the term “correlated” to discuss the relationship found in
the GWAS. Thisis a colloquial use of the term “correlated.” In a strict statistical sense,
correlations describe relationships between two quantitative variables. Here, because the
variables are categories and not numbers, the term that should be used is “associated”
(which is used throughout the “Student Handout”). You may need to clarify this statistical
language with your students.
• The study featured in the news release in Part 1 of the activity is Cadieu et al. (2009). This is
the same studydescribed in Part 5 of the activity. If your students are comfortable reading and
analyzing scientific papers, consider having them read the original paper to learn more about
the study and its findings.
• Consider showing students how GWAS data is plotted; an example can be found in the
“Integrative Genomics Viewer” from the Broad Institute. GWAS data is often shown as a
“Manhattan plot” with SNPsrepresented as dots and color-coded by chromosome.
o In a Manhattan plot, the x-axis shows the locations of the SNPs in the genome, and the yaxis is typicallythe negative logarithm of the P value for the association between the SNP
and the trait. Stronger associations have smaller P values and thus larger negative
logarithms of the P values. So, the higher thedot is on the y-axis, the more significant the
SNP’s association with the trait.
• Consider showing students scientific papers describing human genomics studies that use
GWAS to identify genes that cause disease. You can also point out additional areas of research
in which GWAS are used, suchas in agriculture.
• This activity could serve as a lead-in to evolution since dogs are an excellent example of artificial
selection.
• Students could write an analysis of the activity as a blog post (on a class blog or individual
student blogs).Students could comment on each other’s blogs to facilitate peer review and
discussion.
• Students could create a “Dog Genotype and Phenotype” infographic, intended for a brochure
or a handoutin a veterinarian’s office. This could be done using free online infographic creation
tools, such as Easelly or Piktochart.
1. Explain what a GWAS is. How are SNPs used in this process?
2. Based on the example data in Part 2, which two SNPs are most closely associated with fur color?
(Hint, the first answer should be the SNP that is completely associated, and the second should
be the next highest.)
3. Consider your answer to question #29. How is this method used in human genetics? [Inferences
may be necessary, or simple research. Remember to cite any sources you use, with the
exception of the lecture notes.]
4. Would you consider dogs a good model organism when studying human genetics? Why or why
not?
5. Using a spreadsheet program, create two column graphs of your gene association data. Either
embed the graph or take a screen shot of the final image and include it here (4 pts.)
6. Write a ‘Results’ section based on your data analysis. Note that this is NOT the methods section;
you actually can’t write that since you don’t know the method used to collect the sequence
data. You can simply refer to ‘sequence data’ with the understanding that the precise
methodology would be included in the Methods section of the paper. The Results section
essentially explains the data images