Probability and ribonucleotides

In summary, the conversation discusses the probability of finding start and stop codons in a sequence of 4 ribonucleotides with equal frequency, as well as the average distance between stop codons in a DNA sequence. The probability of a start codon is 1/64 and for a stop codon it is 3/64, but this is dependent on the organism and GC content. The average distance between stop codons is 64/3 codons or 64 nucleotides. The question of start codon probability is deemed irrelevant as it is dependent on the location of the stop codon. Additionally, it is clarified that a codon is made of 3, not 4 nucleotides, and within
  • #1
Yann
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There's question in Hardt's Essential Genetics that bugs me, because I'm not sure if the answer is very simple or if I just don't get the question right. If you have a sequence of 4 ribonucleotides (with equal frequency), what is the probability to have a start codon/stop codon and what would be the average distance between stop codons in a DNA sequence...

The probability of a start codon is 1/64, it's 3/64 for stop codons (of course it depends on the organism but in this case it must be the "convenctional" start/stop codons). A codon is made of 3, not 4 nucleotides. Within a sequence of 4 codons, there could be 2 codons (XXXY or YXXX), so it seems the probability would be 2/64 and 6/64, but I'm not sure if it's that simple...

For the average distance it's easier; 64/3 codons or 64 nucleotides.
 
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  • #2
The probability of codon frequency is dependent on the GC content. To make life easier, suppose GC content is 50%. Then, the probability of a stop codon is indeed 3/64. Asking for the probability of a start codon is a dumb question and is dependent on the locations of the stop codon. Even the naive approach to gene finding first choose the longest regions without stop codons, then look for the start codon.
A codon is made of 3, not 4 nucleotides. Within a sequence of 4 codons, there could be 2 codons (XXXY or YXXX)

That made no sense. Within a sequence of 4 codons, there are four codons - not two. If you meant that within a sequence of 4 nucleotides, there are two codons, that's not true either - there are four. Two in the 5' to 3' direction and two in the 3' to 5' direction.

As for average distance, assuming a GC content of 50%, I agree with your answer.
 
  • #3


Your question is a valid one and it shows that you are thinking critically about the problem. The answer is not as simple as just dividing the number of possible codon combinations by 64. The reason for this is that the start and stop codons are specific sequences that are necessary for proper protein synthesis. In most organisms, the start codon is AUG and the stop codons are UAA, UAG, and UGA. This means that out of the 64 possible codon combinations, only 1 out of 64 will be a start codon and 3 out of 64 will be stop codons. Therefore, the probability of having a start codon in a sequence of 4 codons is 1/64 and the probability of having a stop codon is 3/64.

To calculate the average distance between stop codons in a DNA sequence, we need to consider the fact that there can be multiple stop codons in a sequence. For example, in a sequence of 12 codons, there could be 3 stop codons (UAG, UAA, and UGA) which would result in an average distance of 4 codons between each stop codon. However, in a sequence of 12 codons, there could also be just 1 stop codon (UAA) resulting in an average distance of 12 codons between stop codons. Therefore, the average distance between stop codons in a DNA sequence cannot be determined without knowing the specific sequence of codons.

In summary, the probability of having a start codon and stop codon in a sequence of 4 ribonucleotides is 1/64 and 3/64 respectively. However, the average distance between stop codons cannot be determined without knowing the specific sequence of codons. Keep questioning and exploring these concepts, it will only deepen your understanding of genetics and probability.
 

1. What is the role of probability in studying ribonucleotides?

Probability plays a crucial role in studying ribonucleotides, as it helps us understand the likelihood of certain events occurring in the context of these molecules. This can range from predicting the likelihood of certain nucleotide sequences forming, to understanding the probability of specific mutations or reactions taking place.

2. How is probability used to analyze ribonucleotide sequences?

Probability is used in various ways to analyze ribonucleotide sequences. One common approach is to use probabilistic models, such as Markov chains, to predict the likelihood of certain sequences forming based on their nucleotide composition. Additionally, probability is also used in statistical analyses to compare and evaluate different sequences.

3. What is the relationship between probability and RNA folding?

The process of RNA folding is highly influenced by probability. This is because the folding of RNA molecules is largely driven by the thermodynamic stability of different structures, which can be estimated using probability calculations. Additionally, the probability of specific base pairing interactions also plays a role in determining the final folded structure of RNA.

4. How does the concept of randomness relate to ribonucleotides?

The concept of randomness is closely related to ribonucleotides, as these molecules are often subject to random mutations and reactions. This can have significant impacts on the overall function and structure of RNA, and understanding the probability of these events occurring is crucial in studying the role of ribonucleotides in biological processes.

5. Can probability be used to predict the behavior of ribonucleotides in living organisms?

While probability can provide valuable insights into the behavior of ribonucleotides, it is important to note that it cannot fully predict the complex interactions and processes that take place in living organisms. Probability calculations can help inform our understanding of ribonucleotide behavior, but they must be combined with experimental evidence and other factors to fully understand their role in biological systems.

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