I do high throughput cloning, so customers of mine want complete, verified genes. There is a shit ton of just stuff that can happen that you can't predict even in the most domesticated organism.
Most recently, a transposon jumped from E.coli into my backbone, and I picked it up during sequence. 6kbp added instantly. Absolutely wack.
Apologies, sometimes I forget that I am on a computing forum. Backbone == plasmid backbone. greazy had a good explanation. I'm trying to clone synthetic DNA into plasmids, so all the junk that is necessary for replication and selection is commonly referred to as the "backbone" or "vector", whereas your insert is usually just called the "insert".
C. elegans is nice for this since you can freeze stocks in glycerol. Labs routinely go and thaw out the main wild-type reference stock if the lab stock has been around for too long.
Now I'm in a fly lab and no one's really figured a good way to freeze a fly stock down for long-term storage. So we're left to just accept some degree of background mutation and generally assume that it's not impacting our experiments too much...
It's worth noting that we've found genetic differences between the N2 wild type strains used by different labs as well, so this is still a problem for C. elegans.
This is a real and important challenge, which is even further exacerbated if you work on microbial organisms. I can easily think of a half dozen times in my own research where we tracked down differences in phenotype between ostensibly isogenic strains from different labs that turned out to be the result of in lab evolution.
Another influence on that type of research is the diet used, those are also standardized and comparisons are only valid if comparing the same formula of diet. That also can skew results as for example at least one of the formulas is devoid of vitamin e, which doesn't really occur in the real world.
I think a better title is 'The world is not static'. I often point this out for gradient descent. We always think of the static world when envisioning gradient descent but the reality is the world is constantly changing and can often actually be adversarial. This means that in the long term gradient descent can actually select for stability and not optimality in a dynamic world (this is where ruts come from I believe). It would be interesting to publish an 'expected halflife' statistic for scientific knowledge, like biological knowledge, that will change over time.
How far are we from being able to synthesize a genome from scratch for a small genome organism (or patch a large region)? Then we can rely on computer memory.
I do high throughput cloning, so customers of mine want complete, verified genes. There is a shit ton of just stuff that can happen that you can't predict even in the most domesticated organism.
Most recently, a transposon jumped from E.coli into my backbone, and I picked it up during sequence. 6kbp added instantly. Absolutely wack.
> Most recently, a transposon jumped from E.coli into my backbone, and I picked it up during sequence. 6kbp added instantly.
Can you explain this more? Are you referring to your actual backbone? How did ecoli meet your backbone and why were you sequencing your backbone?
Backbone refers to the cloning plasmid.
Plasmids are grown inside of bacteria which have their own genome with all sorts of oddities like transposons.
Transposons are 'jumping' bits of dna that can insert themselves (given the right criteria is met).
So a transposon(s) from the E. coli genome inserted itself into the plasmid.
This causes all sorts of problems for people who use them to clone (insert) dna into them.
Apologies, sometimes I forget that I am on a computing forum. Backbone == plasmid backbone. greazy had a good explanation. I'm trying to clone synthetic DNA into plasmids, so all the junk that is necessary for replication and selection is commonly referred to as the "backbone" or "vector", whereas your insert is usually just called the "insert".
Thanks for the explanation that’s very interesting.
C. elegans is nice for this since you can freeze stocks in glycerol. Labs routinely go and thaw out the main wild-type reference stock if the lab stock has been around for too long.
Now I'm in a fly lab and no one's really figured a good way to freeze a fly stock down for long-term storage. So we're left to just accept some degree of background mutation and generally assume that it's not impacting our experiments too much...
It's worth noting that we've found genetic differences between the N2 wild type strains used by different labs as well, so this is still a problem for C. elegans.
biology is hard
no, biology is fuzzy.
It’s like wushu. To be externally fuzzy you must be internally complex.
This is a real and important challenge, which is even further exacerbated if you work on microbial organisms. I can easily think of a half dozen times in my own research where we tracked down differences in phenotype between ostensibly isogenic strains from different labs that turned out to be the result of in lab evolution.
Another influence on that type of research is the diet used, those are also standardized and comparisons are only valid if comparing the same formula of diet. That also can skew results as for example at least one of the formulas is devoid of vitamin e, which doesn't really occur in the real world.
I think a better title is 'The world is not static'. I often point this out for gradient descent. We always think of the static world when envisioning gradient descent but the reality is the world is constantly changing and can often actually be adversarial. This means that in the long term gradient descent can actually select for stability and not optimality in a dynamic world (this is where ruts come from I believe). It would be interesting to publish an 'expected halflife' statistic for scientific knowledge, like biological knowledge, that will change over time.
How far are we from being able to synthesize a genome from scratch for a small genome organism (or patch a large region)? Then we can rely on computer memory.