Rough draft.This research track is under review with Dr. Atit's lab. Content and sequence may still change.
The Baby Mateo Case
Genetics domainMedical Interventions (MI), with PBS overlapLesson 6 of 20Your seat: Bioinformatician
Looking Up a Variant
Discovery question
When we find a DNA change in a patient's gene, where do we look it up, and how do we decide if it is harmful, harmless, or unknown?
💡 A database call is built from the weight of evidence and can change as new evidence comes in; frequency is a major clue.
The plan
Prerequisite check
Before this page, you should know
- IRF6 is the gene, and it makes a -factor .
- A variant is a change in DNA, and not all variants are harmful.
If not, review
Today's new idea is only
Today's new idea is only this: a database call (pathogenic, benign, or VUS) is built from the weight of evidence and can change as new evidence comes in.
Learn first
What you will learn
Goal: Students will navigate ClinVar and OMIM and classify a variant entry as benign, pathogenic, or a .
Know by the end
- ClinVar (NIH) stores individual DNA variants and the conditions they have been linked to, each with a clinical-significance call.
- OMIM catalogs genes and the inherited diseases they cause; IRF6 maps to two diseases, (#119300) and popliteal pterygium syndrome (#119500).
- The three clinical-significance calls are pathogenic, benign, and .
- A change common in healthy people is usually benign, while a rare change concentrated in affected families is a red flag; calls can change as evidence accumulates.
- gnomAD (the Genome Aggregation Database) is the healthy-population yardstick: it reports how often a variant appears in tens of thousands of mostly healthy people, so a damaging change that is absent there is a red flag for pathogenic.
Learn first
Model: A ClinVar-style table and an OMIM-style card for IRF6
A simplified ClinVar-style table for IRF6, with real variants from the literature: Entry A is R84C, linked to popliteal pterygium syndrome (PPS), called Pathogenic, recurrent in about 70 families. Entry B is R250X, linked to , called Pathogenic, reported in multiple families. Entry C is V274I, used as a common tag marker, called Benign, common (3% of Europeans, 30% of Asians). Entry D is a brand-new change no one has reported, not established, called a , seen once in one new patient.
OMIM is a second database that lists a gene and the named diseases it causes. The IRF6 card connects one gene to two disorders: IRF6 to (VWS1, OMIM #119300) and IRF6 to popliteal pterygium syndrome (PPS, OMIM #119500). Every database entry carries a clinical-significance call, and that call is built from how often a change appears in patients versus healthy people, family patterns, lab tests, and prior reports.
Learn first
Background and an analogy
Background you need first
- A variant is just a specific change in the .
- How common a change is in healthy people is a major clue to whether it is harmful.
An everyday analogy
A library catalog tells you whether a book is shelved, checked out, or not yet catalogued, but it only knows what librarians have recorded so far.
How it maps: ClinVar is the catalog. Pathogenic and benign are settled records; a is a book not yet catalogued, waiting for more information before it gets a shelf.
Do the work
Explore (work the model before reading on)
- Which two entries are labeled Pathogenic, and what conditions are they linked to?
- How often has Entry C (V274I) been seen in the population, and what is its database call?
- In OMIM, how many different diseases does the single gene IRF6 connect to?
- Compare Entry C (seen in up to 30% of people, Benign) with Entry A (about 70 families, Pathogenic). Why might a change found in nearly a third of healthy people be called harmless, while a rarer change is called harmful?
- Entry D was seen only once and no one has reported it before, so the database cannot call it benign or pathogenic. What does that tell you about how a call gets made?
- Suppose three more labs report Entry D in children who also have clefts, never in healthy relatives. How might the database call for Entry D change, and why?
- In one sentence, what pattern did your team find about how a database decides whether a DNA change is benign, pathogenic, or uncertain?
The plan
Guided notes
1
Two databases
Model start: ClinVar stores individual variants and their condition links; OMIM stores the link between a gene and the diseases it causes.
- ClinVar (NIH) stores individual DNA ____ and the conditions they have been linked to.
- OMIM stores the link between a ____ and the named diseases it can cause; IRF6 maps to VWS and PPS.
2
The three calls
- Pathogenic: strong evidence the change ____ disease (example IRF6 R84C, linked to PPS).
- Benign: evidence the change does NOT cause disease, often because it is ____ in healthy people (example IRF6 V274I).
- : not enough evidence yet to call it either way.
3
How a call is built
- A call is built from ____ (frequency in patients versus healthy people, family patterns, lab tests, and prior reports).
- Calls can ____ as new evidence comes in; a VUS today can become pathogenic or benign tomorrow.
Explore
Reading the Research
What to read
Read the abstract of Leslie et al. (2012) on IRF6 variants. Notice the same gene shows up in both Van der Woude and the more severe popliteal pterygium syndrome. Leslie EJ, et al. 2012. IRF6 variants in VWS and PPS. Genet Med. [PMID:23154523]
Why this source matters
It shows real IRF6 variants and the conditions they cause, which is exactly what a ClinVar entry summarizes one variant at a time.
Words to unlock first
Reading moves
- Skim the title and abstract first to get the gist.
- Circle the one sentence that states the main claim.
- Box the evidence the authors give for that claim.
- Mark one sentence that confuses you, and move on.
Stop point
You do not need the statistics or every variant in the tables. Stay with the idea that a call rests on the weight of evidence.
Your output
Write one claim-evidence sentence about why a brand-new, never-reported IRF6 variant should be classified as a VUS right now.
Lab day
Using the database (what to capture)
Part of today's expected outcome is to actually open the tool below and write down the value it gives you. That captured value is the evidence you will use in your Claim, Evidence, Reasoning. Follow the steps, use the labeled screenshot so you do not get lost, and record each field.
ClinVar
Open the tool Lists DNA variants that have been reported, the condition each is linked to, and a clinical-significance call.
When you use this: Use this when you have a specific DNA change and need to know whether anyone has reported it before and whether it was called harmful.
What the screen looks like
Step by step
- 1Open ncbi.nlm.nih.gov/clinvar and search IRF6[gene].
- 2Open one variant from the list (for example R84C).
- 3Read its clinical significance and the review status (how many labs agree).
Capture these fields
- Variant name: R84C (or c.250C>T)
- Condition: Popliteal pterygium syndrome
- Clinical significance: Pathogenic
- VUS vs pathogenic call: Pathogenic, not a VUS, because it recurs in many affected families
How to read it: A pathogenic call means strong evidence the variant causes disease; benign means evidence it does not; a means there is not enough evidence yet. A call can change as more families are reported, so always note the date.
Lost? ClinVar overview OMIM
Open the tool Catalogs genes and the inherited diseases they cause, with a stable number per entry. It is a professional database; use MedlinePlus Genetics as the student-friendly fallback if access stalls.
When you use this: Use this when you have a gene and want the full list of named diseases it causes and how they are inherited.
What the screen looks like
Step by step
- 1Open omim.org and search IRF6, then open the gene entry (#607199).
- 2Scroll to the phenotype (disease) table.
- 3Read the diseases linked to the gene and the inheritance pattern.
Capture these fields
- Gene entry (MIM number): IRF6, #607199
- Disease(s) it causes: Van der Woude syndrome (#119300); popliteal pterygium syndrome (#119500)
- Inheritance: Autosomal dominant
How to read it: One gene can map to more than one named disease. OMIM ties the gene to its conditions and inheritance pattern, so you know what to expect in a family.
Lost? About OMIM (professional database; use MedlinePlus fallback if blocked) gnomAD (Genome Aggregation Database)
Open the tool A reference catalog of DNA variation from many thousands of mostly healthy people. It tells you how common a variant is overall and within each ancestry group, plus how tolerant a gene is to being broken.
When you use this: Use this when you must decide whether a variant is harmful. A change that damages a but is essentially absent from healthy people is a red flag for disease; a change common in healthy people is almost certainly harmless. gnomAD is the healthy-population yardstick.
What the screen looks like
Step by step
- 1Open gnomad.broadinstitute.org and search the gene IRF6, or paste a specific variant.
- 2Read the global (how often the change appears across all people).
- 3Open the populations breakdown to see the frequency by ancestry, and check the gene constraint scores (is tolerated?).
Capture these fields
- Variant or gene searched: IRF6 R84C (or the gene IRF6)
- Global allele frequency: 0 (absent), or a very small number like 0.00001
- Frequency by ancestry: Differs by group; for example rs642961 is ~0.11 in African and ~0.27 in Native American samples
- Gene constraint (LOEUF / pLI): IRF6 is constrained: a low LOEUF / high pLI means broken copies are not tolerated
How to read it: A damaging variant that is absent or extremely rare in gnomAD's healthy population is consistent with being pathogenic; a variant that is common in healthy people is evidence it is benign. A constrained gene (low LOEUF, high pLI) means losing a working copy tends to cause disease, so loss-of-function changes there deserve extra weight. Because frequencies differ by ancestry, always read the per-population numbers, not just the global one.
Lost? How to read gnomAD (constraint and frequency)Where this fits
Tested on (Ohio WebXam)
Genetics of Disease · 072130
PLTW lesson
MI · Genetics domain · Unit 2 How to Screen Your Genes, 2.1 Genetic Testing and Screening
WebXam domain
Bio-Molecular Technology
Evidence to produce
Given a patient's IRF6 change reported in no database, write the call you would record right now using the three categories and name the one piece of evidence you would most want next to move it off uncertain.
Lab / skill
Medical Interventions (MI) · Principles of Biomedical Science (PBS)
Explore
Vetted readings for this lesson
- Kondo S, et al. 2002. IRF6 mutations cause VWS and PPS. Nat Genet. [PMID:12219090]
- Leslie EJ, et al. 2012. IRF6 variants in VWS and PPS. Genet Med. [PMID:23154523]
- ClinVar (NIH), query gene IRF6
- OMIM IRF6 (#607199); VWS1 #119300; PPS #119500 (professional database; use MedlinePlus Genetics if blocked)
- gnomAD (Broad Institute), gene IRF6: allele frequency in healthy populations
The plan
Track your progress today
Check these off as you work through the lesson, then submit. This tells Mr. Mendoza how you're doing so he can help the class. It does not replace turning in your producible.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
Check off as you finish
- Read the Model and answered the Explore questions.
- Filled in the guided notes in my own words.
- Defined the new vocabulary with an example.
- Opened ClinVar and OMIM and gnomAD (Genome Aggregation Database) and recorded the value it gave me.
- Built the producible: Given a patient's IRF6 change reported in no database, write the call you would record right now using the three categories and name the one piece of evidence you would most want next to move it off uncertain.
- Wrote my Claim, Evidence, and Reasoning exit ticket.
Pick your period and code first.
Check yourself
Exit ticket (Claim, Evidence, Reasoning)
- Claim: A brand-new, never-reported IRF6 variant should be classified as ____ (benign / pathogenic / VUS) at this moment.
- Evidence: The database shows ____ about how often it appears and what conditions it is linked to.
- Reasoning: Therefore the call is ____, because a classification depends on the weight of evidence and can change as more is gathered.
How this is graded (rubric)
For: Given a patient's IRF6 change reported in no database, write the call you would record right now using the three categories and name the one piece of evidence you would most want next to move it off uncertain.
| Criterion | Proficient | Developing | Beginning |
|---|---|---|---|
| Complete | Every required part of the artifact is present and filled in. | Most parts are present, but one is missing or left blank. | Several parts are missing. |
| Accurate | The science and data are correct and match the evidence. | Mostly correct, with a small factual slip. | Key science or data is wrong. |
| Scientific reasoning (CER) | States a claim, backs it with specific evidence, and explains the reasoning. | Has a claim and evidence, but the reasoning is thin or missing. | Gives an answer with no evidence or reasoning. |
| Professional communication | Clear, organized, and labeled the way a clinician or scientist would write it. | Readable but disorganized or missing labels. | Hard to follow. |
| Submitted | Turned in the right way (Schoology for routine work) and confirmed. | Turned in, but in the wrong place or unconfirmed. | Not turned in. |
How the model answer scores against this rubric
- CompleteProficient: Nothing is left blank: the model fills every part of "Given a patient's IRF6 change reported in no database, write the call you would record right now using the three categories and name the one piece of evidence you would most want next to move it off uncertain.".
- AccurateProficient: Every number and claim matches the case evidence.
- Scientific reasoning (CER)Proficient: It names a claim, cites the specific evidence, and explains the reasoning, not just the answer.
- Professional communicationProficient: It is organized and labeled like a real chart note.
- SubmittedProficient: It would be turned in on Schoology and confirmed.
Explore
Where this leads: careers
Bioinformatician Clinical molecular geneticist Variant scientist
What's next: When we read variants we saw codes like R84C and R250X. What kinds of typos in DNA do those codes actually stand for?