Tag Archives: Hardy Weinberg

Your modelling career…

Last week I burbled briefly on Genetic Drift and said I would return to Hardy Weinberg in a future post. Well, here it is… (in a curious case of deja vu, part of me is convinced I’ve already written about this, but can find no evidence! if you’ve read this before, just put it down to advancing senility…).

I think most students find Hardy Weinberg difficult. It’s abstract, it’s got an equation that just seems circular and self-referencing, and it’s hard for teachers to avoid a chalk and talk approach followed by lots of practice of number crunching.

There are some super resources to help with this and I reckon you could usefully get your class to teach themselves the entire topic from this Pearson LabBench Activity.

But, as you know, I like my lessons to involve students doing things, and especially I like making them think. So I came up with this lesson plan.

First, the Powerpoint. What’s wrong with this woman?

Allele frequency intro

Of course, they can’t tell there’s anything wrong just by looking, though they come up with some very creative guesses.

The only clue is in her ethnic origin. Usually, at this point, someone gets sickle cell anaemia. Time out to talk about sickle cell anaemia, why it is a bad thing, and how it is inherited. A picture of a normal vs sickled cell, and then a heterozygote genotype.

The next slide shows a population – stress population – of individuals of varying genotypes. But we’re not going to count individuals, we’re going to count alleles.

The slide helpfully separates them to aid this. I get them to count the HbN alleles, and right at the start it’s worth pointing out the basic principle that they don’t then have to count the HbS alleles – if they know one, they know the other!

We then work out frequency. Easy, isn’t it? Again, look, if you know one, you don’t have to work out the other – they have to add up to 1.

Back to the population. What about the next generation? Are all of those individuals going to pass on their alleles? Why not? We quietly vanish the HbSHbS genotype. What’s the effect on the respective allele frequency?

So, there’s the setting. We’re looking at allele frequency in populations.

Now it’s time to start the modelling. The sheet…

Modelling Allele Frequency in Populations

introduces them to HardyWeinberg without any attempt to explain or use the equation. That can come later. For now, we’re interested in this assumption that allele frequency doesn’t change (you can demonstrate this quite nicely with a pack of cards dealt into pairs, picked up and shuffled, and re-dealt). The exercise mentions the assumptions required, and describes 3 of them. The idea of the exercise is for them to identify 4 more.

The rest is fairly self-explanatory. They divide into pairs, count out some coloured beads, and play around with them as per the instructions. You could talk a little bit about why this kind of thing can only be done as model, rather than an experiment. But they get practice in counting model alleles and working out frequency so they become very comfortable with the process.

The bit they will find difficult is imagining what events these might represent in real life. But with a bit of discussion, a bit of prompting, they figure it out. So for the first event, what could cause half your population (with their alleles!) to disappear overnight? For the second event, what can you say about the blue allele? Why aren’t those alleles being passed on? The third and fourth are more straightforward, though it helps to stress the correct terminology.

And you can then have a discussion about how realistic HW is and when/why you might find allele frequencies changing at a higher rate. This exercise …

Changes in Allele Frequency in real life

gives a few ideas.

I also wasn’t aware until recently that HardyWeinberg assumptions can be used to assess the accuracy of DNA sampling in a population. The slides here show the results of two genotypic assaying samples. You want to check whether they are valid samples. So you compare the numbers given to the Hardy Weinberg equilibrium. What does this tell you about the two samples?

HW assay

That’s enough for now. We’re being inspected and I think that’s someone at the door of the lab….


One spin off from the BTOY award was being invited to chair a series of talks on Biology in the Real World at this year’s ASE conference in Birmingham. It was my first time at this event and it was brilliant. Indeed, I’ll be back next year, if I can wangle the time off, as I was only there for the day and didn’t have nearly enough time to explore everything that was going on. But the overall effect was energising, exciting, inspiring – I came back to Oxford buzzing with new ideas and a bag bursting at the seams with bumpf. Many thanks to the Royal Society of Biology for the invite…

The talks were brilliant – here’s the briefest of summaries….

  1. Professor Joanna Verran (Manchester Uni) on Biofilms. Amazing images of e.g. 1000s of bacterial cells on a single grain of sand
    1. www.erc.montana.edu/CBE
    2. https://student.societyforscience.org/articles/slime-cities
    3. I, SuperOrganism – popular book on human body’s biofilms
    4. Fascinating stuff on quorum sensing and possible role in bacterial control
    5. 99% of planet’s bacteria live in biofilm communities.


  1. Dr Charles Lane (FERA and SAPS) on Killer Plant Diseases.
    1. Great practical on SAPS website on how to demonstrate Koch’s postulates with rotten apples
    2. Ash dieback first plant disease to be discussed in COBRA meeting


    3. Professor Saffron Whitehead (Society of Endocrinology) on Hormones and Homeostasis

    1. Steroids highly conserved – found across Animal Kingdom
    2. Ketoacidosis only occurs in Type 1 Diabetes (because ketone body production inhibited by insulin)
    3. Glycosylated haemoglobin main problem from diabetes leading to similar complications of CVD

4. Professor Greg Hurst (University of Liverpool) on Microbial Partners

  1. e.g. 10-20% of human calorific intake from bacterial digestion in gut (short chain fatty acids – acetate, propionate, butyrate)antibiotics bad for cows/horses because e.g. horses get 80% plus of calories from bacterial digestion. aphids have specialised organ for cultivating symbiotic bacteria that make essential amino acids lacking in phloem – 200 million year old symbiosis. desert rats eat leaves of creosote bush – only because their bacteria detoxify the creosote – a desert rat on antibiotics becomes sensitive to creosote
  2. breast mile contains complex polysaccharides specifically to encourage growth of particular bacteria
  3. aphids not found in tropics because bacteria temperature sensitive
  4. insects dependent on blood/phloem become sterile if fed antibiotics – because they rely on bacteria to produce vital nutrients otherwise lacking in diet
  5. apologising for breaking wind is taking responsibility for the microbial part of you, as methane/hydrogen sulphide are only produced by bacterial enzymes
  6. Review of idea of Holiobionts and how organisms can borrow skills from other Kingdoms by forming a symbiosis/symbiosis opens up new ways of life/niches

5. Dr Ginny Acha (Association of the British Pharmaceutical Industry & British Pharmacological Society) on Personalised Medicines

  1. Interesting data on efficacy of drugs – numbers show percentage of patients who do not respond to drugs for that condition
  • Anti-depressants 38%
  • Diabetes 40%
  • Arthritis 50%
  • Alzheimers 70%
  • Cancer 75%
  • Nice review of history of understanding of blood cancer and how increasing understanding has led to more effective treatment
  • 100 years ago – “disease of blood” – 100% mortality
  • 80 years ago – leukaemia vs lymphoma
  • 60 years ago – 3 types of leukaemia and 2 types of lymphoma
  • Today – too many classifications to note down! 70% survival

Back at school and a lovely lesson with my Year 13s, exploring Genetic Drift through retinitis pigmentosa on Tristan da Cunha (use Google Earth to dramatically show the geographic isolation of this volcanic island)and a rather splendid colour worm game, followed by allele frequency and selection with sickle cell anaemia Sickle Cell Anaemia change in allele freq.

I came up with the idea of applying rates of mutation through Sean B Carroll’s excellent The Making of the Fittest where he does the same with colour vision in birds (brilliant chapter!). It works quite well but, boy, do they struggle with calculating the probabilities! How do you get on?

One way to help is to rephrase the problem. If the rate of mutation was 1 base in 3,000,000,000, what would be the probability of any one person having that mutation? So if the rate is 175 in 3,000,000,000….? And so on. Of course, a point mutation will only have an effect if it’s the right point mutation…. so what do you have to do to the probability?

I send them off to do some homework on Eugenics and applying Hardy Weinberg to the elimination of cystic fibrosis by selective breeding eugenics worksheet with Hardy Weinberg. Yields dramatic results!

I’ll say a bit more about Hardy Weinberg next week, as it’s a nice example of how to make what appears to be dry and theoretical into a hands on, student led learning activity.

But there’s also an Inspection next week, so if it seems a bit rushed, you’ll know why!