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15.7: Limitations of Phylogenetic Trees - Biology

15.7: Limitations of Phylogenetic Trees - Biology



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It may be easy to assume that more closely related organisms look more alike, and while this is often the case, it is not always true. For example, the phylogenetic tree in Figure 1 shows that lizards and rabbits both have amniotic eggs, whereas frogs do not; yet lizards and frogs appear more similar than lizards and rabbits.

Another aspect of phylogenetic trees is that, unless otherwise indicated, the branches do not account for length of time, only the evolutionary order. In other words, the length of a branch does not typically mean more time passed, nor does a short branch mean less time passed— unless specified on the diagram. For example, in Figure 1, the tree does not indicate how much time passed between the evolution of amniotic eggs and hair. What the tree does show is the order in which things took place. Again using Figure 1, the tree shows that the oldest trait is the vertebral column, followed by hinged jaws, and so forth. Remember that any phylogenetic tree is a part of the greater whole, and like a real tree, it does not grow in only one direction after a new branch develops.

So, for the organisms in Figure 1, just because a vertebral column evolved does not mean that invertebrate evolution ceased, it only means that a new branch formed. Also, groups that are not closely related, but evolve under similar conditions, may appear more phenotypically similar to each other than to a close relative.

Head to this website to see interactive exercises that allow you to explore the evolutionary relationships among species.

15.7: Limitations of Phylogenetic Trees - Biology

It may be easy to assume that more closely related organisms look more alike, and while this is often the case, it is not always true. If two closely related lineages evolved under significantly varied surroundings or after the evolution of a major new adaptation, it is possible for the two groups to appear more different than other groups that are not as closely related. For example, the phylogenetic tree in Figure 1 shows that lizards and rabbits both have amniotic eggs, whereas frogs do not yet lizards and frogs appear more similar than lizards and rabbits.

Figure 1. This ladder-like phylogenetic tree of vertebrates is rooted by an organism that lacked a vertebral column. At each branch point, organisms with different characters are placed in different groups based on the characteristics they share.

Another aspect of phylogenetic trees is that, unless otherwise indicated, the branches do not account for length of time, only the evolutionary order. In other words, the length of a branch does not typically mean more time passed, nor does a short branch mean less time passed— unless specified on the diagram. For example, in Figure 1, the tree does not indicate how much time passed between the evolution of amniotic eggs and hair. What the tree does show is the order in which things took place. Again using Figure 1, the tree shows that the oldest trait is the vertebral column, followed by hinged jaws, and so forth. Remember that any phylogenetic tree is a part of the greater whole, and like a real tree, it does not grow in only one direction after a new branch develops.

So, for the organisms in Figure 1, just because a vertebral column evolved does not mean that invertebrate evolution ceased, it only means that a new branch formed. Also, groups that are not closely related, but evolve under similar conditions, may appear more phenotypically similar to each other than to a close relative.

Head to this website to see interactive exercises that allow you to explore the evolutionary relationships among species.


Branch Length and Time

Another aspect of phylogenetic trees is that, unless otherwise indicated, the branches do not account for length of time over which evolution occurred. Rather, they reflect the evolutionary difference and the order of divergence among lineages. In other words, a long branch does not typically mean more time passed nor does a short branch mean less time passed, unless the data are specifically correlated to time with an evolutionary model. A phylogenetic tree may not indicate how much time passed between the evolution of amniotic eggs and hair. What the tree does show is the order in which things took place. For example, the tree in the diagram above shows that the oldest trait is the vertebral column, followed by hinged jaws, and so forth. Remember, any phylogenetic tree is an evolutionary hypothesis that represents part of the greater whole. The individual branches do not necessarily evolve at the same rate or in the same way. So, simply because a vertebral column evolved does not mean that invertebrate evolution ceased. It only means that two lineages diverged. Also, groups that are not closely related, but evolve under similar conditions, may appear more similar to each other than to a close relative.


Seeing the forest for the trees: the limitations of phylogenies in comparative biology. (American Society of Naturalists Address)

The past 30 years have seen a revolution in comparative biology. Before that time, systematics was not at the forefront of the biological sciences, and few scientists considered phylogenetic relationships when investigating evolutionary questions. By contrast, systematic biology is now one of the most vigorous disciplines in biology, and the use of phylogenies not only is requisite in macroevolutionary studies but also has been applied to a wide range of topics and fields that no one could possibly have envisioned 30 years ago. My message is simple: phylogenies are fundamental to comparative biology, but they are not the be-all and end-all. Phylogenies are powerful tools for understanding the past, but like any tool, they have their limitations. In addition, phylogenies are much more informative about pattern than they are about process. The best way to fully understand the past-both pattern and process-is to integrate phylogenies with other types of historical data as well as with direct studies of evolutionary process.


2.16 Species & Phylogenetic Trees

It is surprising that, given the frequency and ease with which the term is used, there is no universally accepted definition of “species.” Historically, and in many contemporary uses, a species is defined as a group of actually or potentially interbreeding populations of individuals. This is the biological species concept and its applications are vast. However, there are limitations to this species definition, as documented in the cases of asexual organisms and hybridizing populations. In addition, proponents of the phylogenetic species concept argue that the reproductive definition is evolutionarily irrelevant instead, a species should be the smallest taxonomic unit, an intact group of organisms that share common ancestry. Yet the point at which one population is considered two distinct species is itself arbitrary, and based on perceived similarities—be they genetic, morphological, behavioral, etc. The situation is further confused by numerous other definitions of species.

In the typical model of speciation, a population is somehow subdivided into two or more allopatric (or physically isolated) populations. These populations experience different mutations, different selective forces and different random events of genetic drift, thus diverging in their evolutionary trajectories. Over time, the populations become sufficiently distinct to warrant identification as separate species. This distinction may be due to some sort of reproductive isolating mechanism, which can be either a pre-mating isolating mechanism or a post-mating isolating mechanism. Pre-mating isolating mechanisms are often behavioral differences (such as bird songs) or habitat preferences that prevent two individuals from courtship or copulation. Post-mating isolating mechanisms often result from genetic incompatibility, whereby offspring may result but they are not viable.

Phylogenies tell an evolutionary story

A phylogeny represents evolutionary relationships between different types of organisms. When we say “turtles, lizards, snakes, birds, and mammals are all amniotes (animals that reproduce with specialized, amniotic eggs), we are speaking phylogenetically.

Figure 2.18 Phylogenetic trees demonstrate the evolutionary relationship between species

We use phylogenetic trees to visualize these relationships (Figure 12.8). In a phylogenetic tree, closely related organisms are joined by nodes. These nodes suggest common ancestry.


15.7 Abortion

It is difficult to have a thorough discussion of baby making without a discussion of abortion. Few topics are more divisive than abortion, especially in countries such as the United States. The controversies surrounding abortion encompass legal, ethical, and moral issues that are beyond the scope of this text (and beyond the expertise of its authors). Thus, our discussion of abortion will be restricted to current abortion methods and then the legal standing of abortion in the United States. This information can help inform both one’s opinions on whether and under what conditions abortions should be legal and whether one considers an abortion a personally acceptable choice. However, this information alone cannot address the ethical and moral questions.

Abortion is defined as the termination of an established pregnancy. Somewhat confusingly, medical personnel sometimes refer to miscarriages (loss of a pregnancy by non-deliberate means) as “spontaneous abortions.” Abortions that are done to purposely end a pregnancy are sometimes called “induced abortions.” In this text when we use the term abortion we are referring to induced abortions.

The vast majority (over 90%) of abortions occur in the first trimester. Abortions within the first trimester can be conducted by the administration of medicine or by physical extraction. Medicinal abortions are done in the U.S. until the 9th or 10th week of pregnancy. The most common medication for this purpose is a combination of pills commonly called RU486. One pill, mifepristone, functions by binding to progesterone receptors. As discussed earlier, progesterone is the hormone that maintains the lining of the uterus during a pregnancy. When the progesterone receptors are bound by this drug, progesterone cannot signal to maintain the uterine lining. The second drug, called misoprostol, causes the cervix to soften and the uterus to contract. Together these drugs cause the uterine lining to shed along with the implanted embryo.

Figure 15.9 Mechanism of medicinal abortion (RU486).

An abortion by physical extraction involves either manual or drug-induced opening of the cervix and the placement of a small tube into the uterus. The tube suctions out the contents of the uterus with suction from a syringe or with a mechanical vacuum pump. Early term abortions that are overseen by qualified medical personnel are relatively safe for the pregnant person (that is, safer than carrying a pregnancy to term).

Second trimester abortions are much less common, and involve a more complicated procedure that involves the scraping of the lining of the uterus. Third trimester abortions are extremely rare and are often the result of life-threatening conditions to the pregnant individual, or discovery of fetal abnormalities that indicate the baby will not survive. The risks of abortion to the pregnant person increase with increasing stages of pregnancy.

In the United States prior to 1973, the legality of induced abortion was determined on a state-by-state basis. However, in 1973 the case of patient “Roe” went to the U.S. Supreme Court after she was denied an abortion in Texas. The lawyers for Roe argued that an abortion fell under medical privacy. The Supreme Court agreed, with the caveat that this right was balanced by the government’s interests in maternal health and potential human life. They determined that the state’s ability to interfere with pregnancy termination was influenced by fetal viability (the potential for the fetus to survive outside the uterus). However, the date at which a fetus is viable is somewhat of a moving metric, depending on medical advances, medical care available, and individual development. Since 1973, many states have instituted some barriers to abortion including waiting periods, mandatory ultrasounds, and counseling prior to abortion. However, the court system has repeatedly struck down bans of abortion during the first trimester of pregnancy or limitations on abortion when the life or health of the pregnant person is compromised. In 2018 and 2019, numerous states (8 as of the publishing of this text, with other states moving in this direction) have passed laws restricting first trimester abortions, including a complete ban on almost all abortions in Alabama. These laws are likely to spend a long time in the court system to determine if they will eventually take effect.

Aside from the legal restrictions on abortion, there are many states that have very few abortion providers, meaning that abortion is not effectively available to people without means to travel. For example, in Mississippi 99% of parishes (counties) do not have an abortion provider. Other states in which more than 95% of counties do not have abortion providers include Nebraska, the Dakotas, Kansas, West Virginia, Wisconsin and Wyoming.


Phylogeny

Adaptation

Phylogenetic trees have become a standard tool in the study of adaptation, and such uses are often referred to as the “comparative method.” First, it is necessary to establish that a particular “adaptation” is distributed as an apomorphy within the group in question and then, if there are multiple origins, to determine if these origins are correlated with other characters and/or environmental variables. While numerous statistical approaches have been suggested for such studies, they all assume that multiple independent origins of characters correlated with environmental or historical factors are evidence of adaptation. Indeed, some workers maintain that it is only possible to discuss adaptation in a historical context, i.e., based on explicit phylogenetic trees. Undoubtedly continued work in these areas will result in improved statistical tests for adaptation based on character distributions on phylogenetic trees.


Tree of life

The (a) concept of the "tree of life" goes back to an 1837 sketch by Charles Darwin. Like an (b) oak tree, the "tree of life" has a single trunk and many branches.

Classical thinking about prokaryotic evolution, included in the classic tree model, is that species evolve clonally. That is, they produce offspring themselves with only random mutations causing the descent into the variety of modern and extinct species known to science. This view is somewhat complicated in eukaryotes that reproduce sexually, but the laws of Mendelian genetics explain the variation in offspring, again, to be a result of a mutation within the species. The concept of genes being transferred between unrelated species was not considered as a possibility until relatively recently. Horizontal gene transfer (HGT), also known as lateral gene transfer, is the transfer of genes between unrelated species. HGT has been shown to be an ever-present phenomenon, with many evolutionists postulating a major role for this process in evolution, thus complicating the simple tree model. Genes have been shown to be passed between species which are only distantly related using standard phylogeny, thus adding a layer of complexity to the understanding of phylogenetic relationships. Finally, as an example of the ultimate gene transfer, theories of genome fusion between symbiotic or endosymbiotic organisms have been proposed to explain an event of great importance: the evolution of the first eukaryotic cell, without which humans could not have come into existence.


16.2. The Reconstruction of DNA-based Phylogenetic Trees

The objective of most phylogenetic studies is to reconstruct the tree-like pattern that describes the evolutionary relationships between the organisms being studied. Before examining the methodology for doing this we must first take a closer look at a typical tree in order to familiarize ourselves with the basic terminology used in phylogenetic analysis.

16.2.1. The key features of DNA-based phylogenetic trees

A typical phylogenetic tree is shown in Figure 16.3A. This tree could have been reconstructed from any type of comparative data, but as we are interested in DNA sequences we will assume that the tree shows the relationships between four homologous genes, called A, B, C and D. The topology of this tree comprises four external nodes, each representing one of the four genes that we have compared, and two internal nodes representing ancestral genes. The lengths of the branches indicate the degree of difference between the genes represented by the nodes. The degree of difference is calculated when the sequences are compared, as described in Section 16.2.2.

Figure 16.3

Phylogenetic trees. (A) An unrooted tree with four external nodes. (B) The five rooted trees that can be drawn from the unrooted tree shown in part A. The positions of the roots are indicated by the numbers on the outline of the unrooted tree.

The tree in Figure 16.3A is unrooted, which means that it is only an illustration of the relationships between A, B, C and D and does not tell us anything about the series of evolutionary events that led to these genes. Five different evolutionary pathways are possible, each depicted by a different rooted tree, as shown in Figure 16.3B. To distinguish between them the phylogenetic analysis must include at least one outgroup, this being a homologous gene that we know is less closely related to A, B, C and D than these four genes are to each other. The outgroup enables the root of the tree to be located and the correct evolutionary pathway to be identified. The criteria used when choosing an outgroup depend very much on the type of analysis that is being carried out. As an example, let us say that the four homologous genes in our tree come from human, chimpanzee, gorilla and orangutan. We could then use as an outgroup the homologous gene from another primate, such as the baboon, which we know from paleontological evidence branched away from the lineage leading to human, chimpanzee, gorilla and orangutan before the time of the common ancestor of those four species (Figure 16.4).

Figure 16.4

The use of an outgroup to root a phylogenetic tree. The tree of human, chimpanzee, gorilla and orangutan genes is rooted with a baboon gene because we know from the fossil record that baboons split away from the primate lineage before the time of the (more. )

We refer to the rooted tree that we obtain by phylogenetic analysis as an inferred tree. This is to emphasize that it depicts the series of evolutionary events that are inferred from the data that were analyzed, and may not be the same as the true tree, the one that depicts the actual series of events that occurred. Sometimes we can be fairly confident that the inferred tree is the true tree, but most phylogenetic data analyses are prone to uncertainties which are likely to result in the inferred tree differing in some respects from the true tree. In Section 16.2.2 we will look at the various methods used to assign degrees of confidence to the branching pattern in an inferred tree, and later in the chapter we will examine some of the controversies that have arisen as a result of the imprecise nature of phylogenetic analysis.

Gene trees are not the same as species trees

Figure 16.5

The difference between a gene tree and a species tree.

The important point is that these two events - mutation and speciation - are not expected to occur at the same time. For example, the mutation event could precede the speciation. This would mean that, to begin with, both alleles of the gene are present in the unsplit population of the ancestral species (Figure 16.6). When the population split occurs, it is likely that both alleles will still be present in each of the two resulting groups. After the split, the new populations evolve independently. One possibility is that the results of random genetic drift (see Box 16.3) lead to one allele being lost from one population and the other being lost from the other population. This establishes the two separate genetic lineages that we infer from phylogenetic analysis of the gene sequences present in the modern species resulting from the continued evolution of the two populations.

Figure 16.6

Mutation might precede speciation, giving an incorrect time for a speciation event if a molecular clock is used. See the text for details. Based on Li (1997).

Box 16.3

Genes in populations. New alleles and haplotypes appear in a population because of mutations that occur in the reproductive cells of individual organisms. This means that many genes are polymorphic, two or more alleles being present in the population (more. )

Figure 16.7

A gene tree can have a different branching order from a species tree. In this example, the gene has undergone two mutations in the ancestral species, the first mutation giving rise to the 𠆋lue’ allele and the second to the ‘green’ (more. )

16.2.2. Tree reconstruction

Sequence alignment is the essential preliminary to tree reconstruction

The data used in reconstruction of a DNA-based phylogenetic tree are obtained by comparing nucleotide sequences. These comparisons are made by aligning the sequences so that nucleotide differences can be scored. This is the critical part of the entire enterprise because if the alignment is incorrect then the resulting tree will definitely not be the true tree.

The first issue to consider is whether the sequences being aligned are homologous. If they are homologous then they must, by definition, be derived from a common ancestral sequence (Section 7.2.1) and so there is a sound basis for the phylogenetic study. If they are not homologous then they do not share a common ancestor. The phylogenetic analysis will find a common ancestor because the methods used for tree reconstruction always produce a tree of some description, even if the data are completely erroneous, but the resulting tree will have no biological relevance. With some DNA sequences - for example, the β-globin genes of different vertebrates - there is no difficulty in being sure that the sequences being compared are homologous, but this is not always the case, and one of the commonest errors that arises during phylogenetic analysis is the inadvertent inclusion of a non-homologous sequence.

Once it has been established that two DNA sequences are indeed homologous, the next step is to align the sequences so that homologous nucleotides can be compared. With some pairs of sequences this is a trivial exercise (Figure 16.8A), but it is not so easy if the sequences are relatively dissimilar and/or have diverged by the accumulation of insertions and deletions as well as point mutations. Insertions and deletions cannot be distinguished when pairs of sequences are compared so we refer to them as indels. Placing indels at their correct positions is often the most difficult part of sequence alignment (Figure 16.8B).

Figure 16.8

Sequence alignment. (A) Two sequences that have not diverged to any great extent can be aligned easily by eye. (B) A more complicated alignment in which it is not possible to determine the correct position for an indel. If errors in indel placement are (more. )

Some pairs of sequences can be aligned reliably by eye. For more complex pairs, alignment might be possible by the dot matrix method (Figure 16.9). The two sequences are written out on the x- and y-axes of a graph, and dots placed in the squares of the graph paper at positions corresponding to identical nucleotides in the two sequences. The alignment is indicated by a diagonal series of dots, broken by empty squares where the sequences have nucleotide differences, and shifting from one column to another at places where indels occur.

Figure 16.9

The dot matrix technique for sequence alignment. The correct alignment stands out because it forms a diagonal of continuous dots, broken at point mutations and shifting to a different diagonal at indels.

More rigorous mathematical approaches to sequence alignment have also been devised. The first of these is the similarity approach (Needleman and Wunsch, 1970), which aims to maximize the number of matched nucleotides - those that are identical in the two sequences. The complementary approach is the distance method (Waterman et al., 1976), in which the objective is to minimize the number of mismatches. Often the two procedures will identify the same alignment as being the best one.

Usually the comparison involves more than just two sequences, meaning that a multiple alignment is required. This can rarely be done effectively with pen and paper so, as in all steps in a phylogenetic analysis, a computer program is used. For multiple alignments, Clustal is often the most popular choice (Jeanmougin et al., 1998). Clustal and other software packages for phylogenetic analysis are described in Technical Note 16.1.

Box 16.1

Phylogenetic analysis. Software packages for construction of phylogenetic trees. Few sets of DNA sequences are simple enough to be converted into phylogenetic trees entirely by hand. Virtually all research in this area is carried out by computer with (more. )

Converting alignment data into a phylogenetic tree

Once the sequences have been aligned accurately, an attempt can be made to reconstruct the phylogenetic tree. To date nobody has devised a perfect method for tree reconstruction, and several different procedures are used routinely. Comparative tests have been run with artificial data, for which the true tree is known, but these have failed to identify any particular method as being better than any of the others (Felsenstein, 1988).

The main distinction between the different tree-building methods is the way in which the multiple sequence alignment is converted into numerical data that can be analyzed mathematically in order to reconstruct the tree. The simplest approach is to convert the sequence information into a distance matrix, which is simply a table showing the evolutionary distances between all pairs of sequences in the dataset (Figure 16.10). The evolutionary distance is calculated from the number of nucleotide differences between a pair of sequences and is used to establish the lengths of the branches connecting these two sequences in the reconstructed tree.

Figure 16.10

A simple distance matrix. The matrix shows the evolutionary distance between each pair of sequences in the alignment. In this example the evolutionary distance is expressed as the number of nucleotide differences per nucleotide site for each sequence (more. )

The neighbor-joining method (Saitou and Nei, 1987) is a popular tree-building procedure that uses the distance matrix approach. To begin the reconstruction, it is initially assumed that there is just one internal node from which branches leading to all the DNA sequences radiate in a star-like pattern (Figure 16.11A). This is virtually impossible in evolutionary terms but the pattern is just a starting point. Next, a pair of sequences is chosen at random, removed from the star, and attached to a second internal node, connected by a branch to the center of the star, as shown in Figure 16.11B. The distance matrix is then used to calculate the total branch length in this new ‘tree’. The sequences are then returned to their original positions and another pair attached to the second internal node, and again the total branch length is calculated. This operation is repeated until all the possible pairs have been examined, enabling the combination that gives the tree with the shortest total branch length to be identified. This pair of sequences will be neighbors in the final tree in the interim, they are combined into a single unit, creating a new star with one branch fewer than the original one. The whole process of pair selection and tree-length calculation is now repeated so that a second pair of neighboring sequences is identified, and then repeated again so that a third pair is located, and so on. The result is a complete reconstructed tree.

Figure 16.11

Manipulations carried out when using the neighbor-joining method for tree reconstruction. See the text for details.

The advantage of the neighbor-joining method is that the data handling is relatively easy to carry out, largely because the information content of the multiple alignment has been reduced to its simplest form. The disadvantage is that some of the information is lost, in particular that pertaining to the identities of the ancestral and derived nucleotides (equivalent to ancestral and derived character states, defined in Box 16.1) at each position in the multiple alignment. The maximum parsimony method (Fitch, 1977) takes account of this information, utilizing it to recreate the series of nucleotide changes that resulted in the pattern of variation revealed by the multiple alignment. The assumption, possibly erroneous, is that evolution follows the shortest possible route and that the correct phylogenetic tree is therefore the one that requires the minimum number of nucleotide changes to produce the observed differences between the sequences. Trees are therefore constructed at random and the number of nucleotide changes that they involve calculated until all possible topologies have been examined and the one requiring the smallest number of steps identified. This is presented as the most likely inferred tree.

The maximum parsimony method is more rigorous in its approach compared with the neighbor-joining method, but this increase in rigor inevitably extends the amount of data handling that is involved. This is a significant problem because the number of possible trees that must be scrutinized increases rapidly as more sequences are added to the dataset. With just five sequences there are only 15 possible unrooted trees, but for ten sequences there are 2 027 025 unrooted trees and for 50 sequences the number exceeds the number of atoms in the universe (Eernisse, 1998). Even with a high-speed computer it is not possible to check every one of these trees in a reasonable time, if at all, so often the maximum parsimony method is unable to carry out a comprehensive analysis. The same is true with many of the other more sophisticated methods for tree reconstruction.

Assessing the accuracy of a reconstructed tree

The limitations to the methods used in phylogenetic reconstruction lead inevitably to questions about the veracity of the resulting trees. Statistical tests of the accuracy of a reconstructed tree have been devised (Hillis, 1997 Whelan et al., 2001) but these are necessarily complex because a tree is geometric rather than numeric, and the accuracy of one part of the topology may be greater or lesser than the accuracy of the other parts.

The routine method for assigning confidence limits to different branch points within a tree is to carry out a bootstrap analysis. To do this we need a second multiple alignment that is different from, but equivalent to, the real alignment. This new alignment is built up by taking columns, at random, from the real alignment, as illustrated in Figure 16.12. The new alignment therefore comprises sequences that are different from the original, but it has a similar pattern of variability. This means that when we use the new alignment in tree reconstruction we do not simply reproduce the original analysis, but we should obtain the same tree.

Figure 16.12

Constructing a new multiple alignment in order to bootstrap a phylogenetic tree. The new alignment is built up by taking columns at random from the real alignment. Note that the same column can be sampled more than once.

In practice, 1000 new alignments are created so 1000 replicate trees are reconstructed. A bootstrap value can then be assigned to each internal node in the original tree, this value being the number of times that the branch pattern seen at that node was reproduced in the replicate trees. If the bootstrap value is greater than 700/1000 then we can assign a reasonable degree of confidence to the topology at that particular internal node.

Molecular clocks enable the time of divergence of ancestral sequences to be estimated

When we carry out a phylogenetic analysis our primary objective is to infer the pattern of the evolutionary relationships between the DNA sequences that are being compared. These relationships are revealed by the topology of the tree that is reconstructed. Often we also have a secondary objective: to discover when the ancestral sequences diverged to give the modern sequences. This information is interesting in the context of genome evolution, as we discovered when we looked at the evolutionary history of the human globin genes (see Figure 15.9). The information is even more interesting on occasions when we are able to equate a gene tree with a species tree, because now the times at which the ancestral sequences diverged approximate to the dates of speciation events.

To assign dates to branch points in a phylogenetic tree we must make use of a molecular clock. The molecular clock hypothesis, first proposed in the early 1960s, states that nucleotide substitutions (or amino acid substitutions if protein sequences are being compared) occur at a constant rate. This means that the degree of difference between two sequences can be used to assign a date to the time at which their ancestral sequence diverged. However, to be able to do this the molecular clock must be calibrated so that we know how many nucleotide substitutions to expect per million years. Calibration is usually achieved by reference to the fossil record. For example, fossils suggest that the most recent common ancestor of humans and orangutans lived 13 million years ago. To calibrate the human molecular clock we therefore compare human and orangutan DNA sequences to determine the amount of nucleotide substitution that has occurred, and then divide this figure by 13, followed by 2, to obtain a rate of substitution per million years (Figure 16.13).

Figure 16.13

Calculating a human molecular clock. The number of substitutions is determined for a pair of homologous genes from human and orangutan: call this number ‘x’. The number of substitutions per lineage is therefore x /2, and the number per (more. )

Despite these complications, molecular clocks have become an immensely valuable adjunct to tree reconstruction, as we will see in the next section when we look at some typical molecular phylogenetics projects.


Limitations of Phylogenetic Trees

It may be easy to assume that more closely related organisms look more alike, and while this is often the case, it is not always true. If two closely related lineages evolved under significantly varied surroundings or after the evolution of a major new adaptation, it is possible for the two groups to appear more different than other groups that are not as closely related. For example, the phylogenetic tree in the figure below shows that lizards and rabbits both have amniotic eggs, whereas frogs do not yet lizards and frogs appear more similar than lizards and rabbits.

This ladder-like phylogenetic tree of vertebrates is rooted by an organism that lacked a vertebral column. At each branch point, organisms with different characters are placed in different groups based on the characteristics they share.

Another aspect of phylogenetic trees is that, unless otherwise indicated, the branches do not account for length of time, only the evolutionary order. In other words, the length of a branch does not typically mean more time passed, nor does a short branch mean less time passed— unless specified on the diagram. For example, in the figure above, the tree does not indicate how much time passed between the evolution of amniotic eggs and hair. What the tree does show is the order in which things took place. Again using the figure above, the tree shows that the oldest trait is the vertebral column, followed by hinged jaws, and so forth.

Remember that any phylogenetic tree is a part of the greater whole, and like a real tree, it does not grow in only one direction after a new branch develops. So, for the organisms in the figure above, just because a vertebral column evolved does not mean that invertebrate evolution ceased, it only means that a new branch formed. Also, groups that are not closely related, but evolve under similar conditions, may appear more phenotypically similar to each other than to a close relative.

Resource:

Head to this website to see interactive exercises that allow you to explore the evolutionary relationships among species.


Watch the video: Ξερίζωμα αμπελώνα (August 2022).