João Gabriel Genova

Essay March 17th: What does replication implies to phylogenetics?

The dichotomous nature of DNA's replication is the cornerstone of phylogenetics. One lineage splitting in two is a reflex of one molecule of DNA duplicating itself. This process is a very delicate one and, to prevent undesired and/or harmful effects, a complex machinery acts repairing whenever a mistake happens. Damage to the DNA can be done in various forms, be it chemical, mechanical or through radiation. Although very efficient, this system is not perfect and sometimes errors can slip through, whenever this happens we call it a mutation. If this mutation can be passed down and spread to the population (thus not being restrained to the individual or molecule where it appeared), it's called a substitution. When a change, or the accumulation of changes, are enough to reproductive isolate one lineage from another, speciation occurs. An issue with our current paradigm is that it is built only based in vertical transfers of information. In nature, mainly in prokaryotes, it's common to have horizontal transfers of genetic material. Albeit knowing how this phenom happens, we are not able to fully understand it under phylogenetic lenses.

Essay March 24th: The Neutral Theory of Molecular Evolution

It’s a common thought that a mutation must be either positive or negative for an organism. In 1968, Mooto Kimura, a Japanese geneticist showed that vast part of mutations in genome are neutral. That implies they are not being fixed through natural selection. Kimura’s Neutral Theory states that random fixation of neutral or very nearly neutral mutations through drift in finite populations is cause behind the majority of evolutionary changes. By neutral we understand that those variants doesn’t interfere in the organism’s fitness. This proposal clashed with the Neo-Darwinians at time, for their thought that natural selection is the main driving force behind evolutionary changes. Data found comparing hemoglobin and other molecules of “living fossils” (organisms that have gone trough few evolutionary chances since they appeared on Earth) with rapid evolving species show that they have undergone the same number of nucleotids substitutions. This evidence gives support to Kimura’s predictions.

references:
Kimura, Motoo (1968) Evolutionary Rate at the Molecular Level. Nature, 217:624.

Essay May 5th: What is tree-thinking?

Tree-thinking is a way to consider objects in a context of descent and inheritance (which can be applied to living and non-living things). In biology, this means working on a phylogenetic basis. Taxa are related through inheritance and descent, sharing common ancestors. If we trace and represent those relationships, we will obtain a tree-like figure. In our tree, the subjects of study are at the tips of the diagram. When we trace the history of the tips, we go down through a branch. The point where branches met is called node, each node represents an ancestor shared by the branches joined there. Does that means that all tips indicate extant organisms? No, fossils and extinct taxa can be placed at tips too. Tree-thinking is such a powerful tool because it informs us of the shared history of our objects and we can plot events that led to divergence between branches to better understand how they affected them. One of the most usual errors in reading evolutionary trees derivate from a tip bias. A being placed right next to B doesn’t mean that they are closely related than B and C. It doesn’t matter who’s alongside who on the top of the tree, what matters is who last shared an ancestor with who.

references:
Baum D. A. & Offner S. 2008. Phylogenics & tree-thinking. The American Biology Teacher, 70:222–229.
O’hara R. J. 1997. Population thinking and tree thinking in systematics. Zoologica Scripta, 26:323–329.

Essay May 12th: Trees and similarity

Suppose you’re a researcher who wants to study the relationships of a genera containing 15 species, how many trees can you build? The answer is in the order of 8,2x1021 . Building all possible trees and analyzing all relevant parameters are near impossible tasks. Even with a computer the time spent would be longer than 10 years. So how can scientists arrive at trees that satisfies their hypothesis amidst this huge forest of possibilities? You can’t look all the trees, but you can search for specific ones. The trick is choosing parameters that narrow down the number of trees. So instead of millions, you end up with a small batch that satisfies the conditions you inputted. The first method proposed for building optimal trees was the UPGMA (Unweighted Pair-Group Method using arithmetic Averages), published by Sokal & Sneath (1963). Under it trees are built by the medium similarity shared between its groups. One main critic about the UPGMA was that it presumes that all changes are equal, something that’s not observed biologically. A solution for this is the Neighbor-Pairing method, developed by Saitou & Ney (1987) which grants different weight to each change.

references
Sokal. R.R. & P.H.A. Sneath. 1963. The principies of numeric taxonomy. W.H. Frceman & Co.San Francisco,Cal.
Saitou N, Nei M. "The neighbor-joining method: a new method for reconstructing phylogenetic trees." Molecular Biology and Evolution, volume 4, issue 4, pp. 406-425, July 1987.

Essay May 19th: Likelihood

Likelihood is a statistical method for estimating the value of a parameter from a set of data. And where does it fit in phylogenetics? There is an array of things that can be estimated such as topologies, branch length and substitutions rates. Those things are the parameters of your model. And as any parameter, they have a lot of values that are possible. So, what are those values? What am I measuring here? People often make a misinterpretation of likelihood values. They read it as a probability of the tree obtained being correct. That’s not true. First, likelihood isn’t a probability. It’s a density function obtained by the distribution of a set of probabilities. Second, it doesn’t indicate how correct a tree is. It tells us the degree of certainty which you can estimate that the event happened.

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