For previous commentary on the same topic, please check here.
The ‘genome project’ team decided to meet in Wisconsin on a nice summer day of mid-April. April 15th used to be the official beginning of summer at the place where I came from, and so I packed my lightest clothes and added only one sweater for ‘just in case’. My flight was through Chicago to Madison and I heard the words ‘snow in Madison’ after reaching Chicago. ‘Will I be able to get out of airport in such cold weather?’ - I started to worry. The airlines quickly solved that dilamma by putting ‘flight cancelled’ notice for my connection. After three hours of frantic phone calls to my collaborator about whether to take Greyhound/rental car or take chance on the following flight to Madison, which happened to be the last flight, I was relieved to leave Chicago on a plane.
Next morning, the entire genome project team met in a conference room at the University. The room was not very big, because there were only seven of us including a graduate student, who was starting his PhD. They were all very good biologists and experts in the organism we planned to work on, but in terms of bioinformatics skills, the most sophisticated ‘bioinformatics program’ everyone was familiar with was Excel. Also, most professors had limited personal grants and access to their local core facilities, where they could do small amount of sequencing.
In traditional genome projects, several biologists, who are domain experts on an organism, meet with a number of sequencing and bioinformatics experts. Biologists share, why the organism is interesting to biologists, and mention anything potentially unusual about the genome (polymorphic, highly repetitive, etc.). Based on their discussion, they jointly write a white paper and submit it to a government grant agency. To see a good example, you may go through the following document -
Our meeting was of similar nature, but right from the beginning, we understood that we could not compete head-to-head with large genome centers solely based assembly quality. However, it was not necessary either. We realized that the genome was only a small piece in a large biological puzzle. If we always kept our sight on the interesting biological properly of the organism and acquired whatever next-gen data was needed to get as close to the truth as possible, we could advance the field equally.
The same difference between traditional genome projects and our bootstrap project is explained below in using ‘management style’ note.
Tradition genome projects: Organism O is biologically interesting. Having a high quality genome for it will advance the field, because many researchers will be able to do genomic experiments. Let us get the best genome for the organism at the lowest possible cost (hence NGS).
Bootstrapped genome project: Organism O is biologically interesting, and we have $X of funds. Let us do the NGS experiments that will get us as close as possible to solving the biological mystery. Genome is an important piece of information, but we will combine genome, transcriptome, evolutionary biology with the sole goal of solving the puzzle.
Sorry for being somewhat abstract in the above description. Our paper will be submitted in a few weeks, after which I will be able to talk more clearly with specific examples.
To be continued.