ಆಯ್ಕೆಮಾಡಿದರೆ, ನಿಮ್ಮ ನಗರ ಅಥವಾ ನಿಖರ ಸ್ಥಳದಂತಹ ಸ್ಥಳ ಮಾಹಿತಿಯನ್ನು ವೆಬ್ ಅಥವಾ ಮೂರನೇ-ಪಾರ್ಟಿ ಅಪ್ಲಿಕೇಶನ್ಗಳಿಂದ ನೀವು ಸೇರಿಸಬಹುದು. ನಿಮ್ಮ ಟ್ವೀಟ್ ಸ್ಥಳ ಇತಿಹಾಸವನ್ನು ಅಳಿಸುವ ಆಯ್ಕೆಯನ್ನು ನೀವು ಸದಾ ಹೊಂದಿರುತ್ತೀರಿ. ಇನ್ನಷ್ಟು ತಿಳಿಯಿರಿ
We have a new paper on bioRxiv today. It’s not a paper I was planning to write during my first semester as a postdoc. https://www.biorxiv.org/content/early/2018/12/13/495275 … (1/n)
Harris et al posted a paper in October called “On the unfounded enthusiasm for soft sweeps II,” in which they presented an alternative explanation for a pattern I observed in my first PhD chapter. https://www.biorxiv.org/content/early/2018/10/19/443051 … 2/
Some background: In 2014, Pennings, Kryazhimskiy and Wakeley published clear, haplotype-based evidence of soft sweeps in response to poor therapies and speculated sweep softness might be related to therapy efficacy. https://doi.org/10.1371/journal.pgen.1004000 … 3/
We followed up and found that early in the HIV epidemic, when drugs failed often due to drug resistance, HIV populations fixed mutations without a loss of diversity. As drugs improved, more diversity was lost after fixation of resistance. 4/
We interpreted this as evidence of a decrease in the population mutation rate, and a shift from soft to hard sweeps. We published this in 2016: https://elifesciences.org/articles/10670 5/
Harris et al claim higher post-sweep diversity after early therapies could be generated if sweeps to bad drugs were slower and followed larger population bottlenecks, while sweeps to good drugs were faster and followed more severe bottlenecks. 6/
Then, recombination could rescue more diversity during sweeps to bad drugs than good ones. Here’s a comparison of our models: 7/pic.twitter.com/NrRU2hPwTB
This is a totally valid hypothesis. It’s one we considered when writing the paper, and I mention it when I give talks about the work. I don’t think it explains diversity maintenance in HIV under bad drugs. 8/
It turns out that HIV fixes mutations in response to bad therapies really quickly and predictably. Here’s some data from ~20 patients treated with FTC in the early 1990s: 9/pic.twitter.com/LBPbjraz9u
In order for resistance to increase so *quickly*, s must be large. When selection is so fast, recombination has little time to operate. 10/pic.twitter.com/DCZHFz1aAj
In order for resistance to increase so *predictably*, theta must also be large. If the probability of a sweep across populations is so high (as it was early in the HIV epidemic), those sweeps are probably soft. 11/pic.twitter.com/UzOzFxOmy9
In summary, Harris et al present a reasonable hypothesis, but it doesn’t fit within the constraints of the HIV system. I think the authors missed some important parts of the HIV literature. 12/
It’s not fun to have your work criticized, but I’m trying to look at the positives of writing the paper: 13/
I had an excuse to try out SLiM (it rocks, @MesserPhilipp + Ben Haller). I read some cool new (well, old) papers. I learned about Rapoport’s rules: https://rationalwiki.org/wiki/Rapoport%27s_Rules … (h/t Noah Rosenberg). 14/
I also had many valuable conversations with colleagues (esp officemate @benjaminhgood and co-authors @pleunipennings and @PetrovADmitri), and I feel like I have a better understanding of the system than when we wrote the original paper. 15/15
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