What a Newfound Kingdom Means for the Tree of Life

In any case, the process consists of basically two steps:

“Align” the DNA of all the species you have sequenced. That’s done using algorithms such as smith-waterman, which minimize the number of edits needed to go from one species’ version of a gene to another.

That number defines a metric that measures all the distances between the species. So, Orang-Utan to Homo Sapiens may be, say, “450”, while Homo Sapiens to Ficus Benjamini is, say “12321”.

(The difference may also be measured on the level of protein sequences. The process is basically the same, only that edits may be assigned different distance scores, because some result in more functional differences, while others are functionally “silent”. Evolutionary pressure would make the first rarer than the latter)

The metric is unitless (I. e. It doesn’t allow translation into, say, “years since species diverged”. But it should fulfill the triangle equality).

Once you have a (triangle) matrix with all the difference, all that’s needed to reconstruct a binary tree that maximizes plausibility, I. E. minimizes the sum of difference at each branching point.

You, dmd, are not going to do anything with the knowledge gleaned from those books, except possibly one of two things: Peruse further study, or inspire others (usually children) to be interested in the field. The book opens up the field, the basic concepts of the field, and a bit of history of the field to you. You now have the tools to go off and either learn more or inspire others. You can even get into conversations and debates with those well-versed in the field.

The book is a gateway into a field, not a path to follow in the field.

That’s a second point, and I should have corrected the start (to “three-ish, since the point on mitochondria is yet another)

If you’re asking specifically about instances of non-treelike gene transfer, the answer is twofold:

First, and I may be mistaken here (I’ve been out of the field for a few years) I think that any metric fulfilling the triangle inequality has a corresponding, consistent tree. So you’ll get a tree, totally. It may just not be the correct one.

Second, if you are asking for our ability to quantify divergence from that model, I’ll give a short explanation of the codon usage method mentioned before as an example:

The genetic code has 4 letters (ACGT) that translates to a different sequence consisting of 21 Amino Acids (a chain of amino acids is a protein, such as the enzymes doing catalysing all the fancy chemical reactions in your body)

Each three letters of DNA code one “letter” of the protein sequence, meaning one amino acid. Since 4^3 > 21, the code isn’t quite optimal.

There are some three-letter sequences that contain meta instructions like start/stop, and some that don’t have any meaning. But there are also instances of two or more three-letter sequences translating to the same amino acid. They are functionally identical. You can replace them in the lab, without any change in phenotype.

For some reason, some species (or even branches in the teee of life) still show preferences for using one or the other three-letter code for a given amino acid.

If you plot which of the (functionally identical) codes are used within a bacterial genome, you can find sudden changes, where the preference switches dramatically for some lenght, then returns to the previous preference.

That’s indicative of a piece of DMA that jumped across the tree. It’s really not very subtle when you know to look for it.

Another, even more obvious, example is viral DNA: this tends to end up as mangled, non-coding (“junk”) DNA, containing (fragments of) genes that often have nothing in common with the rest of the DNA, but have long stretches nearly identical to, say, a known gene for some viral coat.

In terms of quantification I’m really at the limits of my memory (and, unfortunately, in-flight internet), but I’ll take a stab and the former mechanism can be found in 5-10% of bacterial genomes, and amount to usually less than 8% of he genome, with maybe one or two exceptional cases with 20% or so (some bacterial species may have developed a tendency to exploit this sort of buffer overflow to cheat at evolution)

Phylogenists (the biologists working in trees, but not those “trees”) do consider all this (and much more). Where they encounter “known unknowns”, you will often see trees with nodes branching into more than two branches. That’s essentially what cartographers would lable “here be dragons”. Or, prosaically: it isn’t quite clear which split happened first in evolutionary history.

Besides, every other model lets students develop incorrect intuitions. Incorrect intuitions are still useful, and by letting students develop intuitions based on more obviously incorrect models like the Bohr model, you are teaching them the same skills they will need to use when they discared Lewis dot diagrams for molecular orbitals, or any other point in the future when established models are replaced. If you can't do that, you’re not doing science, and if you can’t teach people how to discard theories, you’re not doing a good job at teaching science.

There is a tendency among the older generation (any older generation, at any given time) to complain about how their children are being taught wrong. Parents will pass onto their children a bunch of facts and skills, only to find out that schools teach something completely different. This is natural, of course. You can’t freeze a curriculum in time and still make it useful, you have to throw some parts of it out. But if you take students through the process of throwing something out, like the Bohr model, they’ll be more prepared for a changing future.

The electron really is a wave-like thing confined a by coulomb potential and thus has a discrete set of solutions. Moreover the discrete indexes of that solution map onto mechanical properties like angular momentum and energy. The Bohr model captures all of that, and even gets the right equations for the energy (at least in simple cases).

Of course the real wave equation that needs solving is much more complicated than the 1-d cartoon in the Bohr model, but that cartoon works because it captures many essential properties of the real system.

But all my peers remember the Bohr model regardless. Because it is simpler, it is easier to remember. People will develop the wrong intuition regardless of what you do. If you start with the complicated ideas, they just give up on learning instead, substituting superstition.

In any case, you can't really do anything with a model of the atom unless you're using equations, and you only get the quantum versions because those are the only ones that work. Everyone else doesn't have any need for a true model of the atom, and thus no incentive to learn it. (Most of the time, you'd rather need a model of molecules.)

I'm not trying to brush off the impact of global warming, I'm just placing it in the context of 1+ billion years of Earth history.

Anything that has survived for a billion years in a form that could still be considered roughly the same organism or a close descendant must have a relatively stable biochemistry and gene pool that is capable of surviving an extreme range of environmental changes - as close as you can get to a holy grail in natural selection.

Obviously its survival would not be inevitable; not even stars can survive their own age.

>Even in science ideas don't win purely on merit. They require marketing and political support too.

Ideally the world would be a meritocratic place, while still offering both sympathy and dignity to the weakest members. Does anyone disagree with that? But still, politics and cheating always weasel their way into power structures of society. And it should be seen as morally reprehensible within science.