We now make a final attempt to find DnaA boxes in E. coli by finding the most frequent 9-mers with mismatches and reverse complements in the region suggested by the minimum skew as ori. Although the minimum of the skew diagram for E. coli is found at position 3923620, we should not assume that its ori is found exactly at this position due to random fluctuations in the skew. To remedy this issue, we could choose a larger window size (e.g., L = 1000), but expanding the window introduces the risk that we may bring in other clumped 9-mers that do not represent DnaA boxes but appear in this window more often than the true DnaA box. It makes more sense to try a small window either starting, ending, or centered at the position of minimum skew.

Let’s cross our fingers and identify the most frequent 9-mers (with 1 mismatch and reverse complements) within a window of length 500 starting at position 3923620 of the E. coli genome. Bingo! The experimentally confirmed DnaA box in E. coli (TTATCCACA) is indeed a most frequent 9-mer with 1 mismatch, along with its reverse complement TGTGGATAA:

aatgatgatgacgtcaaaaggatccggataaaacatggtgattgcctcgc ataacgcggtatgaaaatggattgaagcccgggccgtggattctactcaa ctttgtcggcttgagaaagacctgggatcctgggtattaaaaagaagatc tatttatttagagatctgttctattgtgatctcttattaggatcgcactg cccTGTGGATAAcaaggatccggcttttaagatcaacaacctggaaagga tcattaactgtgaatgatcggtgatcctggaccgtataagctgggatcag aatgaggggTTATACACAactcaaaaactgaacaacagttgttcTTTGGA TAActaccggttgatccaagcttcctgacagagTTATCCACAgtagatcg cacgatctgtatacttatttgagtaaattaacccacgatcccagccattc ttctgccggatcttccggaatgtcgtgatcaagaatgttgatcttcagtg

You will notice that we emphasized a large part of this sequence with bold text. This region is the experimentally verified ori of E. coli, which starts 37 nucleotides after position 3923620, where the skew reaches its minimum value.

We were very fortunate that the DnaA boxes of E. coli are captured in the window that we chose. Moreover, while TTATCCACA represents a most frequent 9-mer with 1 mismatch and reverse complements in this 500-nucleotide window, it is not the only one: GGATCCTGG, GATCCCAGC, GTTATCCAC, AGCTGGGAT, and CTGGGATCA also appear 4 times with 1 mismatch and reverse complements.

STOP and Think In this chapter, every time we find ori, we seem to find some other surprisingly frequent 9-mers. Why do you think this is?

We do not know what purpose — if any — these other 9-mers serve in the E. coli genome, but we do know that there are many different types of hidden messages in genomes; these hidden messages have a tendency to cluster within a genome, and most of them have nothing to do with replication. One example is the regulatory DNA motifs responsible for gene expression that we will study soon. The important lesson is that existing approaches to ori prediction remain imperfect and are sometimes inconclusive. However, even providing biologists with a small collection of 9-mers as candidate DnaA boxes is a great aid as long as one of these 9-mers is correct.

Thus, the moral of this chapter is that even though computational predictions can be powerful, bioinformaticians should collaborate with biologists to verify their computational predictions. Or improve these predictions: the next question hints at how ori predictions can be carried out using comparative genomics, a bioinformatics approach that uses evolutionary similarities to answer difficult questions about genomes.

STOP and Think Salmonella typhimurium is a close relative of E. coli that causes typhoid fever and foodborne illness. After having learned what DnaA boxes look like in E. coli, how would you look for DnaA boxes in Salmonella enterica?

Thank you for reading this far! We have covered a lot of material, but the chapter isn't finished yet. Each chapter in this book is accompanied by an epilogue (see the next lesson) considering additional practical considerations or complications of the central question. If you have completed the code challenges, then the epilogue terminates with a "Final Challenge" asking you to get your hands dirty and apply what you have learned to a real dataset. We hope that you will see how tricky dealing with raw biological data can be!

A Final Attempt at Finding DnaA Boxes in E. coli