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Nothing in evolution makes sense except in the light of biology - Coggle…
Nothing in evolution makes sense except in the light of biology
Introduction
Evolutionary biology is the key to understanding how life came to be, amazing adaptations and where individuals are vulnerable. This research explains why individuals share physicals and genetic features, and show's a large history of research.
Evolution is predictable based off of 2 types of data, empirical and theoretical. Examples include gene predictability of change if under the same selective pressures, seen in sunflower species. As well as the sticklebacks in freshwater habitats lose their sines.
Examples of evolution being unpredictable is the phenotypic response of predation in Bahama mosquito fish, selection favors a single function under selection will not be able to tell what the actual response will e and when it will occur since evolution is so random it is hard to predict.
Prediction is used to understand the diversity of niches over time of species, yet in the example of birds at high altitudes that have a larger oxygen capacity, the changes of nucleotides and amine acids causes this and that change is unpredictable.
Why do we want to predict evolution?
If we can predict evolution in new species, climate change, infectious diseases that are emerging quickly, and environmental changes it is critical to do so now.
Prediction of which animal will go extinct or how their genotype will help them adapt is helpful for a conservative point of view, prediction of when and here a pesticide will occur will help farmers, prediction of drug resistance helps human health as well as the trajectory of covid-19 and how well distancing works and level of virulent.
Troubles with production include knowing the prediction on all levels of biology, an example is E.coli, the evidence shows hat adaptations and transportation can be redactable but genes and mutation types are not predictable.
What it means to predict
Forecasts are quantitative and are based on models or historical data that can be interpreted to help the future with estimates or error.
The word predict can be used very loosely, using a variety of ideas. "Predict" is derived from the Italian word "Predicate" which means prior to say. The definition of predict is that action of declaring something before it actually happens.
Predictions are not trivial, for example the increase in fitness will be equal to the genetic variation. This shows that there is genetic variation for traits that affect fitness selection needs to impact genetic drift, and a change in environment, and competition reduces fitness at a faster rate than adaption happens.
Hypothesis 1
Evolution can not repeat itself and evolution is not predictable at the molecular and population level.
Mutations can be predictable when talking about transversions and hotspots but they are unpredictable when determining when or where they will occur. This problem is due to the fact that evolution is dependent on random actions. The counter argument to this problem is that in large populations, mutations will occur regularly.
When there is selection on a standing genetic variation it becomes easier to predict because meiosis causes recombination which adds stochastic variation, new linked alleles, mutations, and chromosomal re-arrangement.
Genetic drift is required for random changes of allele frequencies. Adults producing offspring is a random chance, beneficial mutations can be eliminated due to failure to find habitat. If offspring do survive then they will get random genes from their parents and cause random changes in allele frequencies.
In context of the distribution and recombination rate of mutations, it can be easy to forecast accounting formation and recombination hotspots but the probability is unpredictable for the immediate future over a long time period. Mutations can arise as well as drift, this shows that evolution can be more predictable in the long therm.
Hypothesis 2
Evolution can be predictable using models and data.
A computer tool called SLiM is able to produce simulations using whole genomes that can show us recombination and migration. This can be used to show a direction of evolution in many different ways, forecasting evolution has two requirements, conceptual progress and data.
Genotype to phenotype prediction in a short term evolution is hard to predict since mutation is so random but over long periods of time or large populations the law of large numbers shows that it can be predictable. This shows that in humans at least 1 new mutation will effect the nucleotide in a genome every year.
A requirement is that with every genetic change will produce a phenotypic change.
Conclusion
Forecasting helps address question and answers them with biological solutions. Examples include forecasting for infectious diseases or extinction prevention.
Biological solutions that are achieved from forecasting include the growth of tumors and how, HIV and the flu, evolve rapidly.
Inherent unpredictability shows an issue for precision so the less precise the more predictable forecasting is time scale dependent.
CSE format
Varki A. 2006. Nothing in Glycobiology Makes Sense, except in the Light of Evolution. Cell. 126(5):841–845. doi:10.1016/j.cell.2006.08.022.