Week 14 Biology Lab & Inquiry: Transcribe & Translate a Gene

Part 1 — The Big Picture

This week you learned that a cell writes a gene's message in the nucleus and reads it at a ribosome in the cytoplasm: DNA → mRNA → protein. RNA polymerase reads the template strand and builds an mRNA with U where DNA pairing would give T, and the ribosome reads that mRNA three bases at a time from the AUG start codon until it reaches a stop. In this lab you do the whole job yourself. You watch one sequence go through transcription and translation in a free interactive, then carry two short lab genes from template to protein by hand with a codon table, scan each message for a stray T, and check the reading frame. Then you test a question about the code itself: does changing one base always change the protein? You make two one-base edits, predict what each will do, and check. Last, you audit a chatbot's account of your lab and catch where it scrambles an order, garbles a count, mislabels a molecule, oversimplifies the code, swaps one kind of cell division for another, or invents a number.

Time budget: Plan for about 120 minutes.

Part 2 — The Task

Guiding question: When one base in a gene changes, does the protein always change, and what does the codon table say about why?

Before you begin — hypothesis: Before you make the edits, write one hypothesis in the if… then… because… form: if one base in a codon of Lab Gene A changes, then the protein will or will not change, because of a reason about the codon table that you can state. Then predict, for each of the two edits in Part 3, whether the amino acid at that position will stay the same or change.

Workshop data: Two lab genes and two one-base edits, printed in this lab

Source: Two short model genes and two one-base edits written for this lab, not real gene sequences; every codon call comes from the codon table printed in Part 3, which follows the standard genetic code.

• Rows: 2 lab genes of 12 bases each plus 2 one-base edits to Lab Gene A, shown as 2 rows in the decoding table and 2 rows in the edit table; the first scaffold table has 5 rows that name the parts of the test rather than data
• Columns: gene, DNA template strand (3′ to 5′), mRNA (5′ to 3′), T count in the mRNA, codon count, protein, and where each step happens
• Unit: bases, codons, and amino acids, each counted one by one

Part 3 — Materials & Procedure

Tools and materials

• Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet)
• The codon table printed in Part 3, and a pencil and paper or a document for your tables
• A document or notebook for your written answers

Ways of working

• virtual-simulation-inquiry
• at-home-protocol-and-data-table
• figure-and-diagram-interpretation

Procedure

1. Open the Learn.Genetics Transcribe and Translate a Gene interactive in your browser and follow its on-screen steps to carry its DNA sequence through transcription and then translation. This is a warm-up; record nothing yet. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: The interactive ends with a chain of amino acids built from its sequence.
2. Before you decode anything, fill in the first table in Part 4: your hypothesis, your prediction for each edit, what you change, what you look up, and what you keep the same. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: The first table has an if… then… because… hypothesis and a prediction for Edit 1 and Edit 2.
3. In a spreadsheet or on paper, write Lab Gene A's template strand, 3′-TAC CGG CTC ATT-5′, one triplet per cell or per line. Under each template base, write its mRNA partner with the rules A → U, T → A, G → C, C → G. Then read your mRNA once looking only for the letter T. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: A 12-base mRNA written from its 5′ end, with a T count recorded in the decoding table.
4. Find the AUG at the start of your mRNA, split the message into codons of three from there, and look up each codon in this table: AUG = Met (start); GCU, GCC = Ala; UAU = Tyr; UUU = Phe; CCC, CCU = Pro; GGA = Gly; GAG = Glu; GUG = Val; GAU = Asp; UAA, UAG, UGA = stop. Write the protein with three-letter names joined by en dashes, and write stop where the chain ends. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: A codon count, a protein, and the stop codon recorded for Lab Gene A.
5. Repeat steps 3 and 4 for Lab Gene B, whose template strand is 3′-TAC GGA AAA ACT-5′. In the last column of the decoding table, name where in the cell each step happens. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: Both rows of the decoding table are complete, with no T in either mRNA.
6. Make Edit 1 on Lab Gene A: change its second template triplet from CGG to CGA. Make Edit 2 on Lab Gene A: change its third template triplet from CTC to CAC. For each edit, write the new mRNA codon, look it up, and record the amino acid before and after in the edit table. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: Both rows of the edit table are complete, and each edit has a verdict: the protein changed or did not.
7. Answer the analysis questions in Part 5, then run the critique step in Part 6 or its equivalent route. Tool: Free virtual labs and simulations (PhET, HHMI BioInteractive, Learn.Genetics), a virtual microscope, and a spreadsheet (Google Sheets or any free spreadsheet). Check: Five written answers and one critique report.

Fallback route

When to use it: Use this route if the Learn.Genetics interactive will not load or your browser cannot run it.

Skip the warm-up in step 1 and complete steps 2 through 7 by hand with the printed codon table; every table, question, and the critique step are the same, and you submit the same items for equal credit.

This route earns the same credit as the primary route.

Part 4 — The Scaffold

Name every part of the test before you decode, so the edits test a prediction rather than confirm a result.

Student scaffold table 1

Part of the test	Your answer
Hypothesis (if… then… because…)
Prediction for Edit 1: will the amino acid change?
Prediction for Edit 2: will the amino acid change?
What you change in each edit
What you keep the same in both edits

Carry each lab gene from template to protein and record where each step happens.

Student scaffold table 2

Gene	DNA template (3′ to 5′)	mRNA (5′ to 3′)	T count in the mRNA	Codon count	Protein	Where each step happens
Lab Gene A	TAC CGG CTC ATT
Lab Gene B	TAC GGA AAA ACT

Record what each one-base edit does to Lab Gene A's codon and amino acid.

Student scaffold table 3

Edit	Template triplet, before → after	mRNA codon, before → after	Amino acid before	Amino acid after	Did the protein change?
Edit 1 (second triplet)	CGG → CGA
Edit 2 (third triplet)	CTC → CAC

Part 5 — Analysis Questions

1. Show the division that gives each gene's codon count and the subtraction that gives its number of amino acids, and say in one sentence why the stop codon is not counted as an amino acid.
2. Compare your two edits. Which one changed the protein, which one did not, and does that result support or fail to support your hypothesis? Write one conclusion sentence that uses supports or fails to support rather than proves.
3. Use the codon table to explain why one edit left the amino acid the same and the other changed it, naming the redundancy of the genetic code, and connect your Edit 2 to the change from GAG to GUG in sickle cell disease.
4. State the central dogma in order with the place each step happens, and explain why the cell sends an mRNA copy out of the nucleus instead of the DNA itself.
5. Choose one and answer it in 3–4 sentences. (a) Your lab genes are 12 bases long and were written for this lab: name one way real genes differ from them, and say what that limits about your conclusion. (b) Your codon table lists only some codons: name one edit you could not have judged with it, and say what you would need to judge it.

Part 6 — AI-Critique Moment

Choose one equal-credit critique route. Route A: ask an approved AI tool to critique your completed work, then check its response against your own evidence. Route B is the no-AI equivalent printed below.

Approved tools: Claude, Gemini, ChatGPT, Grok, Microsoft Copilot.

Prompt to paste:

I've pasted my completed Week 14 Biology Lab & Inquiry tables above. I transcribed two short model genes from their DNA template strands into mRNA, translated each with the standard genetic code, and then changed one base in two places to see whether the protein changed. Please do six things. First, put transcription and translation in order and name the part of the cell where each one happens. Second, check my codon count and my amino-acid count for each gene, showing each division and subtraction. Third, say which molecule carries the codon and which carries the anticodon. Fourth, tell me whether every one-base change in a gene changes the protein, and explain why or why not. Fifth, name the kind of cell division that makes the egg and sperm cells that pass a gene to offspring, and say how many cells it makes. Sixth, tell me the exact number of genes a human cell transcribes every second, with its source.

Test the response for these likely failures:

• Chatbots sometimes put translation before transcription, or place translation in the nucleus.
• Chatbots often count the stop codon as an amino acid, reporting 4 amino acids from a 12-base message, or mix up the code's 64 codons with the 20 common amino acids.
• Chatbots sometimes put the anticodon on the mRNA or write a T into an mRNA as if it were DNA.
• Chatbots often say every one-base change alters the protein, skipping the codon table's redundancy.
• Asked the callback question, chatbots sometimes say mitosis makes the egg and sperm cells, or that it makes four cells.
• Asked for a rate, chatbots often state a precise number of genes transcribed per second and cite a study or source that was never given.

Write 3–4 sentences: name one thing the chatbot got right, quote at least two errors it made, and correct each one with evidence from your tables or Chapter 14.

Equivalent route (no AI required)

No AI account is required for this lab. Instead of the chatbot, critique this flawed analysis, printed here in full: "Lab Gene A's template TAC CGG CTC ATT gives the mRNA ATG GCC GAG TAA, which has 12 bases, so 4 codons and 4 amino acids. Translation happens first, in the nucleus, and then transcription carries the protein out to the cytoplasm. The anticodon sits on the mRNA. Every one-base change alters the protein, so both edits must change it. Genes are copied into mRNA only while a cell divides by mitosis, which is also how egg and sperm cells are made. A human cell transcribes about 40 genes every second, according to a study." Mark it up: quote each flawed sentence, name what is wrong (a mis-ordered process, a garbled count, a mislabeled structure, an over-simplified mechanism, a mitosis-for-meiosis swap, or an invented figure), cite the evidence from your tables or this week's chapter, and write a corrected sentence beneath it. This route assesses the same objectives (Objective 7 and Objective 3) as the chatbot critique, takes comparable effort (about 30 minutes and 200–300 words), is scored by the same scoring criteria for the same credit, and its own submission artifact is the marked-up flawed analysis, submitted in place of the critique report and share link.

Part 7 — What to Submit

• All three completed scaffold tables
• Written answers to all five analysis questions
• The chatbot critique report with its share link, or the equivalent route's marked-up flawed analysis

Deliverable:

A short Biology Lab & Inquiry report on transcribing and translating a gene: three completed tables (the named parts of the test, the two lab genes carried from template to protein with T counts, codon counts, proteins, and locations, and the two one-base edits with their before-and-after codons and amino acids), written answers to five analysis questions, and a critique of a chatbot's account of your lab, or, on the equivalent route, a marked-up correction of the printed flawed analysis. Submit in any accessible file type or as a link; a recorded response may be submitted as audio or video with a transcript, or as text. Choose a written, recorded, or visual form for your answers; every form is graded by the same scoring criteria.

Rubric

The rubric below shows how each submitted part is evaluated; bands are full, partial, or none.

Workshop evaluation criteria

Criterion	Full	Partial	None
Testable hypothesis and the parts of the test	A falsifiable if… then… because… hypothesis and a prediction for each edit appear before the edits, and what is changed and what is kept the same are named.	A hypothesis appears but is not falsifiable or lacks the edit predictions, or what is changed or kept the same is missing.	No hypothesis, or the parts of the test are not named.
Decoding table: template to mRNA to protein	Both mRNAs are paired correctly with no T, each is split into codons from AUG, each protein is read correctly from the table with the stop written as stop, and the places of transcription and translation are named.	The table is filled, but one or two pairings, codon calls, counts, or locations are wrong, or a T appears in an mRNA.	No decoding is recorded, or the sequences are copied from a chatbot rather than paired by hand.
Edit table and the redundancy of the code	Both edits show the correct new codon and amino acid, the verdict for each is correct, and the result is tied to several codons coding for one amino acid.	One edit is worked correctly, or both are worked but the verdicts are not tied to the codon table.	No edits are worked, or the verdicts are stated without any codon evidence.
Analysis: counts, order and place, and the limit	All five questions are answered with the counts shown, the central dogma ordered with its places, a conclusion that uses supports or fails to support, and a real limitation.	Three or four questions are answered well, or a count is unshown, or the conclusion says proves.	Fewer than three questions are answered, or the answers do not use the lab's evidence.
Critique of the chatbot or of the printed flawed analysis	On either route, at least two errors are quoted, each is named by kind, and each is corrected with evidence from the lab tables or the chapter; both routes earn this band equally.	On either route, only one error is caught and corrected, or errors are named but left without evidence.	On either route, no critique appears, or the text is submitted with no error identified.

Quality Gate

• Every mRNA is built base by base from the printed template and carries no T.
• Every codon call comes from the printed codon table, never from memory or a chatbot.
• Each codon count shows its division and each amino-acid count shows its subtraction.
• The hypothesis and both edit predictions were written before the edits were made and use the if… then… because… form.
• Transcription is placed in the nucleus and translation at a ribosome in the cytoplasm, in that order.
• No sequence, rate, percentage, study, or source is invented anywhere in the submission.
• The critique quotes the chatbot or the flawed analysis and corrects at least two errors with evidence from your tables or the chapter.