- We want to develop rigorous prediction of how molecular drive could cause preferred sequences to accumulate, so we've developed a computer simulation model of it.
- How the model works. Fig. 2 = schematic diagram.
- Why we focus on equilibrium properties, and how we identified equilibria. Fig. 3 = approach to equilibrium from above and below.
- Effect of the mutation rates of the genome and the recombining fragments. Fig. 4A = Mutation rates don't affect equilibrium scores.
- Effects of the amount of recombination per cycle. Fig. 4B = Amount of recombination limits uptake sequence accumulation.
- Effect of minimum cutoff for recombination. No figure.
- Effect of matrix strength (100-fold and 10-fold bias) and scoring algorithm (additive and multiplicative scoring of fragments). Fig. 5A = matrix effects; Fig. 5B = additive and multiplicative scoring effects.
- Using the Gibbs Motif Sampler to identify and characterize uptake sequences in the N. meningitidis and H. influenzae genomes. Fig. 6? (and other genomes - Fig. S1)
- Proportions of perfect and singly-mismatched uptake sequences in simulated genomes and in real genomes characterized by the Gibbs sampler. No figure, but maybe a table of frequencies.
- Spacing of uptake sequences in simulated and real genomes. Fig. 7A&B = simulated genomes; 7C&D = N. meningitidis and H. influenzae genomes.
- Simulation of DUS and USS evolution using Gibbs-derived matrices. Fig. 8A&B = uptake sequences accumulate to high frequencies; logos are like those of the corresponding real genomes.
- We thus expect the genome motifs to correspond to the uptake biases, but we see serious discrepancies with published H. influenzae uptake measurements (comparable data for N. meningitidis is not available ). We redid these experiments, and see the same discrepancies. Fig. 9 = Lindsay's uptake assays.
- Might the problem be that recombination is affected by other biases (in addition to the single-base effects studied so far)? Test for covariation between DUS/USS positions reveals very little. Fig. 10A&B = covariation.
- Measures of USS variation in H. influenzae populations also reveal effects of all biases that ultimately influence what recombined into the genome, but these are also discordant with the observed genomic bias. Fig. 11A&B = BLAST analysis of simulated and real genomes.
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Course Corrections5 months ago in Angry by Choice
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The Site is Dead, Long Live the Site2 years ago in Catalogue of Organisms
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The Site is Dead, Long Live the Site2 years ago in Variety of Life
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Does mathematics carry human biases?4 years ago in PLEKTIX
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A New Placodont from the Late Triassic of China5 years ago in Chinleana
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Posted: July 22, 2018 at 03:03PM6 years ago in Field Notes
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Harnessing innate immunity to cure HIV8 years ago in Rule of 6ix
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WE MOVED!8 years ago in Games with Words
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post doc job opportunity on ribosome biochemistry!9 years ago in Protein Evolution and Other Musings
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Growing the kidney: re-blogged from Science Bitez9 years ago in The View from a Microbiologist
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Blogging Microbes- Communicating Microbiology to Netizens10 years ago in Memoirs of a Defective Brain
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The Lure of the Obscure? Guest Post by Frank Stahl12 years ago in Sex, Genes & Evolution
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Lab Rat Moving House13 years ago in Life of a Lab Rat
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Slideshow of NASA's Stardust-NExT Mission Comet Tempel 1 Flyby13 years ago in The Large Picture Blog
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in The Biology Files
Not your typical science blog, but an 'open science' research blog. Watch me fumbling my way towards understanding how and why bacteria take up DNA, and getting distracted by other cool questions.
Damn, reordering the US-variation manuscript yet again...
Sudden realization that I've been stupidly persisting with a stupid topic order. Here's the new order of the Results:
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