average gene length in prokaryotes (part 1)

One of my side research projects involves processing large numbers of genomes (specifically, all fully-sequenced prokaryotic genomes). Since I’m playing with the data anyway, sometimes I end up with random questions that can be answered with what I already have on hand. One such question is this: “What is the average length of a prokaryotic gene?” We could figure this out fairly directly, but it’s always best to have a prediction in hand first. After all, if we have no idea what kind of values to expect, how can we trust the accuracy of a more direct (and experimental) method?

So what do we know? There are 4 possible bases (A, G, C, and T) and three such bases make up a codon. This means that each position of the codon can be any of 4 bases, so there are 4*4*4 = 64 possible codons. Of these, 3 are stop codons (meaning that they mark the end of a gene). We generally think of there being only 1 start codon (ATG, coding for methionine), but it turns out that prokaryotes often use other codons instead. Plus, if there are multiple ATG’s in the same stretch of DNA, how do we know which is the actual start?

For example, take the sequence:


This sequence has two potential start sites (in bold) and two stop codons (in bold italics). We can unambiguously choose the first stop codon, but we have no way of knowing without more evidence which start codon is the real one.

To get around this, let’s take a conservative approach in calling sequences a “gene”. Instead of anything beginning with a start codon and ending with a stop, let’s take the entire genome and blast it to bits by cutting at every stop codon.

Continue reading


This post discusses a computer program that you can download to try yourself (and get the source code if you want to make your own version).

At a family reunion earlier this summer, we were handed a wordfind that someone had generated somewhere on the Internets that contained the names of the family founders. I was solving mine and noticed that, as anyone has frequently observed, in any given wordfind you will find words that are not in the list. Presumably, this is due to the randomly-assorted letters, by chance, spelling out an unplanned word. Of course, the wordfind makers might also stick those in on purpose (for example, the family wordfind contained the website name multiple times) or purposely prevent some random words (profanity). Regardless, I began to wonder how often a word might appear in a word find just by chance. So I used the margins to scratch out a formula for the chance of finding a word of a certain length within a matrix of random letters.

Continue reading