This page last changed on Mar 17, 2008 by chaddorsey.
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  Content or Topic User Actions Software considerations Instructional goals & considerations
1.0 Dragon Intro & Overview
1.1 Mendelian overview
User sees two dragons, breeds them to get one offspring.
User notices that traits can be dominant or recessive. (Questions here.)
User introduced to chromosome view - Mendelian traits.
User prompted to make changes to see effects. User answers questions/ perf. assess about Mendelian heredity.
1.2 Clinical traits? Where do these come in? Clinical traits - introduce them here? Randy: this is just a number... (Need to introduce this as a concept)
1.3 Meiosis
User introduced to meiosis view for this breeding.
User manipulates individual chromosomes to cause steps in meiosis.
User zooms during meiosis first stage to closer view of doubled chromosomes.
Notes presence of genes on chromosomes and doubling of these as exact copies.

Genes shown here in some diagrammatic manner.
Create view of zoomed tetrads both with and without recombination. Include genes on this view as extended segments within chromosomes? Chromosomes are graphical representations of underlying data, but information about user interaction with them is not currently captured for use within Pedagogica scripting. For example, we may wish to prompt a student to click on a chromosome in the meiosis view and call up the corresponding DNA view. This is not currently possible, and will need to be added.
Breakdown to meiosis - view of what is happening here
1.4 Genome level
User then enters the gene/allele-level view of chromosomes.
User identifies the genes seen in the initial Mendelian breeding portion.
User manipulates single-allele-controlled trait to note changes.
Consider using a drop-down type menu here, to avoid confusion created by ability to delete and add alleles.  
1.5 Recombination

Now with recombination:
Pause meiosis at various stages - note what they see?
Students examine two-paned view w/meiosis on one side and gene view on other - relate the recombination to genetic basis.

Task: Create a tailored recombination so offspring inherits a designated trait
User should use information from the chromosomes, and be able to specify the point at which recombinations will occur. This does not currently exist, though some ability to control crossing over does exist. This should be looked into. Also, in this section, defining how the results of meiosis translate to the resulting organism will require being able to "force" the choice of a specific gamete for fertilization. This is currently not included. Understand how recombination happens

Be able to appreciate the phenotypic effects of recombination
2.0 Section 2
2.1 Crossing & Intercrossing

Auto-generate medium-sized population of recombined crosses.

User compares individuals within this cross by stacking chromosomes and noting variety of differences. User compares these to phenotypes of generated dragons.

Make variety of crosses between various dragon strains?

Examine these crosses for similarities and differences

Interbreed individuals from a strain and stack chromosomes - identify similarities here. Interbreed another generation and note similarities.
The notion of strains is not currently defined in Biologica – this will need to be donw, so that multiple organisms can be looked at simultaneouslyl. When this is the case, we would like to be able to "stack" selected chromosome from many individuals for visual comparison across individuals. Understand how strains develop over generations and relate this to the genetic characteristics.

Discover markers in the process

Appreciate what a strain is on the genetic level
2.2 Genetic Markers
Note visibility of markers - notice that they are close to certain genes.
Discover phenotype linked to marker - make link that it must tie phenotype to a gene, but not clear which gene b/c of ambiguity of link.

Make series of crosses - note that markers stay close to genes in cases where markers are correlated with phenotype and not in others.

Tabulate some marker-gene pairings that would be useful for future "experiments."
How do we want to do genes? How big? Notice that markers mark a larger stretch of the chromosome that contains a gene.

Notice that they are generally inherited with the genes. (Does this mean we have a situation in place where genes are already tagged to markers?)

Establish necessity of linkage between markers and genes for usefulness

Experience in some way the idea that we can only target these markers, not the genes.
3.0 Section 3
3.1 Understanding QTL QTL steps distilled:

• Identify (create?) two distinct strains, one that exhibits trait and one that doesn't
• Breed a cross between the two strains A and B to get a crossed population with a significant number of individuals
• Measure the phenotype in each individual - this tends toward "high" or "low," but values vary, rather than being binary.
• Find the average phenotype value for the population.
• Also find these average phenotype values for intercrossed populations of the strains A and B
• Now look at markers: Imagine we have a marker on chromosomes 1, 2 and 3 of all individuals. User will look at genotypes for all three populations.
• Examining markers, user compares differences in phenotype with marker genotypes. This is done by grouping the individuals' chromosomes into "parent A," "parent B," and "mixed" groups, then calculating the average value of the phenotypes for each group.
• The user repeats this regrouping and averaging for each of the three markers.
• To analyze the findings, the user calculates the difference between the "high-parent" and "low-parent" phenotype averages for each marker, then creates a histogram of values with three bars, one for each of markers 1-3.
• Upon examining this histogram, the user notices that the differences for Markers 1 and 3 are relatively low, but that the differences are stark for Marker 2.
• From this, the user can infer that this marker #2 is useful for tracking the phenotype. Individuals who have inherited two copies of Marker 2 that is the same as in the "high"-phenotype parent, exhibit high phenotype values. For those with markers matching the "low" parents', the phenotype average value is low. For those mixed, it is intermediate. Examination shows that variation exists within these populations, but that the overall trend is clear.
• The same connection does not exist (or only slightly) for markers 1 and 3. As a result, the user can see that marker 2 is "connected" to the phenotype much more than the other two markers.
• The user looks at the chromosome near the marker and finds two genes there. Researching more, the user finds that one of these genes is known to control a condition related to the phenotype under examination. The user identifies this gene as the gene likely responsible for this phenotype as well.

• Variations on this to increase nuances and complexity:
o Ambiguous example in which two markers have equally high values, so that the gene library is more important.
o Example in which the gene library results are ambiguous, but analysis of a second group overlaps with this one to help narrow the area under consideration to a useful one.
o Examples with many more individuals and many more markers - these may be introduced separately or together.

Can we drag and drop these genotypes within a stack, so students can rearrange them themselves? Can we click on a marker and have it vertically highlighted through a stack, so we can compare a large set of individuals?  
3.2 Level 1: Dragon Model Species
3.3 Scenario - Identification of desired trait

Introduction of problem

Model species

User learns of difficulties with dragons - dying or contracting disease of some sort

Dragons live too long to be studied for this, unfortunately. However, another similar species has short lifespans - intro model species
Introduction of problem

Model species

Establish utility of having model species

User views schematic/visualized DNA of dragons and that of "drakes," identifies similarities. Possiblly identifies some shared functions/diseases/features?

How could these be useful? User led to/reminded of previous scenario, identifies genetic analysis of drakes as potential to unlock answers.

QTL analysis as key to solving

Initial solution process.

Statistics/necessary numbers of individuals for QTL

User given set of drakes that possess a similar disease and set that don't. Problem posed: what to do? How can these be used to help solve the problem?

User breeds cross of strains of affected and unaffected dragons: correct direction.

Statistics interlude: Will we get an answer from only one pair? (Notebook from before should be stacked to show that multiple trials are necessary.) Establish that we will need a large number of these.

User breeds 200 back-/inter-crossed individuals from two strains.

QTL analysis

QTL "machine" introduced (or introduced from previous section). User uses this to run one-QTL analysis on the bred population.

Results - ambiguous? Clearly two peaks. One narrow and one broad.

3.8 Gene browsing/ background literature
Gene of drakes/dragons too complex to view in detail with this - introduce gene browser here?

User investigates narrow peak in gene browser. Literature/previous research and knowledge introduced. User must interpret research to identify that this gene is not the desired gene for the process. (How do we know this definitively?)

3.9 Combining results of multiple QTL scans

Back to broad peak. Other strains introduced. User can run scans of these as well. Possibly distribute this work among classmates?

Two QTL scans produce two areas of interest that are similar, but not quite the same. (Possibly this step is what causes us to look away from the initial narrow peak, BTW. It's not in the second scan? A hit against it...)

User combines these two scans into a single, narrower peak.

Will require additional software support to do this in some way.
Gene browsing with results

Back to gene browser again.

With narrowed focus, two separate genes are within the area of interest. When looking into research done on these genes, one is clearly not of interest, but the other is implicated in similar diseases and related to iron deficiency. Voila.
4.0 Level 2: Mice
4.1 Initial scenario/intro
Mouse genome introduced (through prompted gene browsing?)
  Introduce students to differences and similarities between mouse and drake genomes.

4.2 QTL scans with mouse genome User led through running one-QTL scan on mouse genome for clear-cut case - revealed that this was published by a scientist. Did they find the same result?   Introduce QTL scanning with mouse genomes

Genome browse for clear-cut case, possibly additional areas of interest included.


Intro to research scenario

Students presented with research scenario: looking at genome for traits linked to _____. Experimental/strain background explained. Students learn that data have been used by scientists previously - they may discover results that scientists have not yet found, and can help verify the findings of the scientists themselves.

Students see the possible data sets - select sets to analyze. (How do they decide? Is there background on any of them? Reasons for selecting one over another? Are they assigned?)

Student runs single-QTL scan on chosen data set. Wide confidence interval.

Can we have a "Show R" button available, to make it possible, but not necessary, to look behind the scenes? (May be a future piece.)

4.4 Present research problem      
4.5 Multiple QTL scan combination Student runs single-QTL scan on second data set. Prompted to notice similar location on this scan, but with different confidence interval.

[Gene browsing? Students discover it's not useful b/c of wide confidence interval.]

Students "discover" each others' findings -(may be posted on a modified forum, transmitted through internal collaboration, other). With access to each others' findings, students combine data to narrow area of interest from 8 scans.

May need tool to help students visualize the overlaps among multiple datasets.

Collaborative tools needed - Key question here: Will these be primitive (forums) or more advanced?
4.6 Overlapping multiple data sets      
4.7 Gene browsing with narrowed interval.
Students use narrowed interval as guide for gene browsing, go to gene browser. Gene narrowable to a small subset of genes. Students can look up previous research on those genes, determine gene they think is responsible for the phenotype.

Students do this within "regular gene browser"? Log their actions as they do so? Not sure if this is local data or MozSwing-type Web foray - hopefully more toward latter.

Gene browsing based upon QTL combined-scan findings

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