Biology IA · A · Unity and diversity · topic 2 of 25
Does heat-loving mean GC-rich? · IB Biology IA idea: guide, sample graph and step-by-step plan
a brave one: honest results winG-C pairs have three hydrogen bonds, A-T pairs only two. So do microbes that live in hot springs pack in more G and C? Check, and be honest about what you find.
- ✓ you like data and spreadsheets
- ✓ you can't get lab time
- ✓ you enjoy a question where the answer may be 'not much'
The big idea
← the answer might be 'weakly'. that's fine!A G-C pair is held by three hydrogen bonds and an A-T pair by two, so it is tempting to predict that heat-loving prokaryotes have GC-rich genomes. The link across whole genomes is known to be weak, so your job is not to confirm the story but to test it fairly. You choose the data, sample across different groups so close relatives do not count many times, apply a suitable correlation test, and report what the data say. A modest result, well argued, can score very well.
Make it yours: pick one twist
Copying a classic won't show your choices. Pick one of these (or invent your own) and your IA becomes yours.
Swipe for more twists →
Take GC content of the double-stranded stem regions of rRNA, not the whole genome.
→ The part of the molecule that must stay folded may track temperature more closely. You compare two kinds of GC and your analysis becomes a comparison of correlations.Analyse bacteria and archaea separately, then together.
→ Tests whether a pattern is real or just reflects which group an organism belongs to. Your graph is split by group.Focus on one well-sampled genus with a wide range of growth temperatures.
→ Removes much of the ancestry problem but cuts your range and sample size. Your evaluation discusses the trade-off.Include genome length as a second variable and see if it confounds the pattern.
→ Two independent variables mean a more complex analysis. Keep it to a simple comparison unless you know the method.Replace GC with another feature such as the proportion of charged amino acids in the proteome.
→ Moves toward protein stability. The data source and calculation change, but the correlation design stays.Your Biology IA research question: run the check
Write your own question first. Then make sure it ticks every box:
- Names both variables (optimum growth temperature and genome GC %) and the range of temperatures (for example 20 to 100 °C).
- Says where each value comes from, and how you match the same strain across sources.
- Says how you will sample so that closely related species do not dominate (which groups, how many per group).
- Says which statistic you will use and why it suits this kind of data.
- Is a question whose honest answer could be 'weak or none', not one that assumes a result.
The workflow
A database investigation has no apparatus, so the 'set-up' is your data pipeline. Draw your own version, with the real sources and filters, for the Method section.
How your Biology IA could be laid out
The usual order for a topic like this, what each part needs to show, and roughly how much of your 3,000 words it takes. The words are all yours.
Your question; why DNA stability and temperature might be linked; what you expect and why.
Base pairing and stability; what is known about GC and growth temperature (cite); why close relatives are not independent.
Independent and dependent variables, and the controls that apply to a database (sources, groups, filters).
Which databases and trait source; the filters; how you chose groups and species; why the sample answers your question; how you match strains.
Short and honest: screen use only; note that data come from published sources and give credit.
The table you analysed, with units, source and date accessed for every value.
How you got GC % and temperature; how you handled missing or conflicting values; one worked example of each calculation, and the ranking step for the test.
Scatter plot suitable for ranked data; the correlation, its sample size and its p-value; what the plot shows by group.
Answer in terms of the strength and direction of the relationship, with the statistic; compare with published studies; limit your claim to the data you used.
Weaknesses of the sampling and of the data sources, which matters most for your answer, and realistic improvements.
Every database (with accession dates) and every paper.
What your Biology IA graph could look like
n = ? write it next to the graphMade-up data, to show you the form of a strong graph, not the answer. Yours will look different. example only
- Each point is one species. Because the values are looked up, not measured by you, there is no error bar; explain that choice.
- Both a weak and a strong relationship are drawn, so the reader can judge your data against them.
- Colour or shape the points by group (for example bacteria and archaea) to show whether one group drives the pattern.
- Report the number of species and the correlation next to the graph, not only the shape of the cloud.
- Another graph to consider: rank the data and plot ranks, or show GC separately for each group with the median marked.
Your game plan
rules for sampling BEFORE you collectTick steps off as you go. We'll remember on this device.
0 of 10 done
- Read and predictFind what is known about GC content and thermal growth in prokaryotes. Write down what you predict and why, and what would count as a weak result.
- Choose your sourcesPick the genome database and a growth-temperature source. Check how each defines its values and how often they are updated.
- Trial run (1 lesson)Try 10 species. Can you match the same strain in both sources? Are the temperatures an optimum or just a range? Fix your rules now.
- Write the sampling rulesChoose groups first, then species within them, and how many per group. Write down why. Decide what you will do with missing or conflicting values.
- Collect the dataFill the spreadsheet straight from the sources. Record the accession or ID, source and date for every value.
- Choose the statisticDecide whether a rank correlation or a regression suits the data. Check what each assumes, and whether your points are independent enough.
- ProcessCalculate the statistic and its p-value, and say what your significance level is. Do one worked example by hand.
- Graph and interpretPlot the data with groups marked. State the direction, strength and sample size, and what the p-value does and does not tell you.
- EvaluateWhich weakness in your sampling or sources mattered most? Make every improvement specific.
- Check before your teacher's draftRun the checklist below, then get your RQ or draft checked. Your teacher reads one draft only, so make it count.
Biology you'll need
Traps to avoid in this Biology IA
- Treating close relatives as separate data points: twenty species from one genus are closer to one data point.
- Matching a genome from one strain with a growth temperature from another.
- Using a growth range as if it were an optimum.
- Writing 'strong correlation' when the statistic says weak, because the story felt right.
- A correlation test used without thinking about whether the data suit it.
- Saying temperature causes the GC value. Correlation is not cause.
More Biology IA ideas like this
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- Species–area on a school field●●○
This guide shows how a topic like this is usually approached. It is not an IA. Your question, choices, data, analysis and words must be your own: change something, tell your teacher where the idea came from, and follow your school's rules on outside help.