Category Archives: evolution

Gene network robustness

pathwaysWhen looking at a map of biochemical pathways (a small part of which is above) one can start to get an idea of how complex a cell is. The protein products of genes carry out these steps to keep the chemistry of a living cell going. Disrupting these pathways by blocking a step with a gene mutations often results in a phenotype and/or in humans what we would recognize as a genetic disease. The genes are turned on and off by the expression of other genes that respond to each other and to biochemical and physical signals in the cell and from the environment by a complex regulatory logic. Furthermore, certain phenotypes and genetic diseases are also caused by, not blocking a biochemical step, but by carrying it out in the wrong place or time during development or in response to environmental stress, etc.

When thinking about this it is easy to believe that cells are highly evolved (which they are) and that making random changes to the system would almost universally result in negative effects (which ... strangely may not be as true as we might think). I like to use a car as an model of a cell in class in various ways. If you know what you are doing you can repair a car to restore its function or even add new functions. However, if you make random changes to a car, even if you just limited yourself to a single system like rewiring the electrical system or shuffling mechanical parts around in the drive train, you are very likely to, if there is any effect at all, mess the car up and render it useless (very rarely you might accidentally improve things).  Using this analogy it is intuitive that shuffling the part of the gene that codes for an RNA or protein product around with the part of the gene that controls its expression (the promoter in a broad sense including regulatory regions that increase or decrease expression by interactions with other molecules) would render the cell useless, in other words result in severe phenotypes and/or lethality.

This perspective is why this article is so interesting to me,
Isalan, M., Lemerle, C., Michalodimitrakis, K., Horn, C., Beltrao, P., Raineri, E., … Serrano, L. (2008). Evolvability and hierarchy in rewired bacterial gene networks. Nature, 452(April), 840–845. doi:10.1038/nature06847.
These authors focused on transcription factors, which are sort of master switches in the cell, the gene products of transcription factors turn other groups of genes on and off. They reshuffled 26 promoter regions with 23 regulatory genes in E. coli (to put this in perspective only nine transcription factors control half of all of the genes in E. coli) and tried 598 possible combinations in a high copy plasmid (small extra chromosome present in many numbers) that was cloned (added to the cell).

In the car analogy parts were not removed and replaced with alterations; rather altered parts were added. Like adding a fifth wheel in a random orientation somewhere along the drive chain, or adding extra wires connected to a random location to the electrical system---still not a good idea for a car. In addition, within the cell some of these new combinations are predicted, based on simplistic understanding of the cellular network, to result in run-away positive or negative feedback loops when interacting with the cells normal machinery (e.g., expression of a gene leads to even more expression of that gene, etc.).

So what happened in E. coli? By my count 20 out of 26x23=598 combinations (Figure 2a) either failed to be cloned or were cloned but failed to grow. A cloning failure could be due to negative effects on the cell, so presumably only 20/598=3.3% of the reshuffled genes could not be tolerated by the cell. (Note, the authors report this number as 30 or approximately 5%; also note, if you are recalculating this, that there is a control row and column in Figure 2a). Flipping this around 95% to 97% of the rewired plasmids were tolerated by the cell, which frankly is astounding. The authors point out in the introduction their surprise that highly interconnected master switch alterations in the cell can be tolerated.

Okay, so laboratory conditions are easy. The cells are grown under ideal conditions and given everything they need. So, most of the cars started up and are idling in the parking lot; what about taking them out for a test drive? The authors compared growth conditions, of the rewired constructs that were tolerated by the cell only 16% differed significantly from the controls in their growth profiles. 84% of the cars that started up seem to be able to accelerate and cruise normally under highway conditions. (At this point you might start to think that some of the changes made were not significant, like scooting back a car seat a few inches; this is not the case, the authors test the the altered genes are indeed expressed and some of them are expressed at levels 100's of times higher or lower than the controls, and remember these are master switches not randomly selected fine scaled tweaks.)

It's time for a greater challenge; lets take the cars to a racecourse and then off road! The authors did repeated rapid transfer of the bacteria to fresh media---the bacteria have to divide quickly to keep up---and 12 of the rewired networks were able to keep up with the controls and these tended to have rewired flhD controls which regulate flagellar genes and gives a clue as to why this might be an advantage (by suppressing the extra energy it takes to activate the flageller system). Next the authors put the cells under conditions where they either had to survive very long periods of time without fresh media or at high temperatures (50°C, 122°F). They found that a rpoS-ompR rewiring combination out-competed the controls under both of these conditions. So, out of only 598 combinations tried, which is a tiny fraction of the total number possible, one novel combination gave a fitness advantage under a new environment.

This has obvious implications for the adaptation of cells to new challenges by rewiring their gene network. But what is still most surprising to me is how well altered networks are tolerated in general. A cell is much more sophisticated than the machines we are used to like cars. It has evolved to buffer changes and make sure the important things get done despite strong disruptions to the system. Here is another network example, this time from yeast, that might help to illustrate this enhanced level of sophistication compared to our intuition of the system.

Cells have to undergo a cycle of growth and division. This cell cycle is controlled by a group of genes. In this paper,
Davidich, M. I., & Bornholdt, S. (2008). Boolean Network Model Predicts Cell Cycle Sequence of Fission Yeast, 3(2). doi:10.1371/journal.pone.0001672
the authors treated the cell cycle control genes as being simply "on" or "off" in the following interaction network where the genes turn each other on or off over a series of time steps.


From a starting configuration of gene activity, the start signal (the cell has grown to sufficient size with enough resources) triggers the activity of the other genes flipping each other on and off and a master process unfolds that directs the actions of other genes (outside of the figure) needed to carry out the steps of the cell cycle and division. At the end of the process the original starting configuration is reset to wait for the next start signal (also have a look at Table 2 in the publication). This is a very simplistic model but it captures essential components of what is known about the yeast cell cycle.

What if the starting configuration is disrupted? Then the wrong cascade of signals would propagate through the network, activating the wrong sets of genes. Without a master record of which switches should be set to on and off at the beginning is the cell doomed to deviate along a different path and not be able to return to appropriate cell cycle? Treating the genes (and the start signal) as simply on or off there are 1024 possible starting configurations. This plot shows how all possible configurations are predicted to transition to and from each other.


The arrows in blue are the normal steps of the cell cycle. From a large number of deviated starting configurations the cell will be able to, within a few steps, predominantly reset itself to the correct cell cycle. This is a property of the network of gene interactions and is not due to random chance. (There are some starting points that do not return to the main path, but also keep in mind that this is a very simplistic model.) This shows that the cell has evolved to be robust to disruptions, even in very subtle ways that may not be obvious at first, such as the wiring of its gene interaction network. Simply looking at Figure 1 above does not imply, to a human, the robustness of the system that is uncovered in Figure 2.

The paper goes on to describe another example of the evolution of gene networks with a different set of interactions of the genes involved in the cell cycle for a different species of yeast (S. cerevisiae vs. S. pombe). The wiring is altered, with a different type of reliance on internal signals, but the end result of robustness of the system is essentially the same.

Difference and similarity: a single gene controls more than one classical evolutionary result.

Two articles just came out in Nature:

"The industrial melanism mutation in British peppered moths is a transposable element"

"The gene cortex controls mimicry and crypsis in butterflies and moths"

pepper2A transposable element insert in cortex is responsible for the classical example of industrial melanism in moths, where a rapid change in phenotype occurred in response to an (human driven) environmental change.  Soot from coal burning causing darkened tree trunks near urban areas of England over the 1800's making it harder for the lighter colored moth to evade predation; this trend later reversed in the 1900's (less pollution and more frequent lighter moths).


This same gene is rapidly evolving and shown to be responsible for shifts in mimicry patterns (where species pairs, one or both of which may be toxic, appear similar to avoid predation, another excellent and now classic evolutionary example) in Heliconius butterflies.


Lamarck and Giraffes!: Closing the Circle

You're going to think I'm nuts but this is too good to pass up!


One pre-Darwinian theory of evolution is credited to Jean-Baptiste Pierre Antoine de Monet, Chevalier de Lamarck (1744 – 1829). One component of his theory was "L'influence des circonstances" (the influence of circumstances) which we take today as an acquired trait (not a genetic trait), like bigger muscles, etc., that is a response to an environmental factor and is transmitted from parents to offspring. This (the transmission of environmentally influenced acquired traits) is referred to as Lamarckism or Lamarckian evolution.

A common example used in textbooks to illustrate this is the length of giraffe's necks. Giraffe's were originally short necked but each generation the adult giraffes would stretch their necks to reach higher leaves that were left behind. Stretching their necks resulted in the adult's neck being slightly longer (than if it had not stretched). Importantly, according to the theory, this trait, longer necks, was transmitted to the giraffe's offspring. Over many generations the necks grew increasingly longer. In Lamarck's view interaction with the environment (circumstance) led to an inherited physical change in the organism.

Okay, so with the modern synthesis of evolution incorporating Darwinian adaptation and Mendelian inheritance, among other things, we can comfortably laugh at this scenario.* However, in recent decades the role of epigenetic inheritance has been increasingly understood. With epigenetics there are not changes to a DNA sequence (mutations as we generally understand them) but "tags" are added to the DNA sequence that alters the expression of a gene. Importantly, factors in the environment the organism is exposed to change how these tags are added and this can be inherited across generations. So, there is a way for an organism's environment to influence inherited physical changes in an organism's future descendants.

A famous example is "agouti" coat color in mice. Mice that are heterozygous for an A[vy] allele have variable phenotypes ranging from yellow to brown, as a result of the influence of environmental effects.


Interestingly, when parents are exposed to compounds like Bisphenol-A (BPA) this can cause a trans-generational shift towards more yellow descendants. On the other hand when the parents diets are supplemented with large amounts of folic acid, vitamin B12, or zinc there is a trans-generational shift towards more brown ("pseudo-agouti") descendants. This has been determined to be because of differences in methylation (one form of the DNA "tags") of a promoter region of the Agouti gene sequence.


There are many more examples of epigenetic effects for a range of traits in a range of species. I am not going to attempt to review them here, but this is an active and interesting area of research and we are just beginning to understand how extensive this might be and the role it might play in, for example, human genetics (think for a moment of all the vitamins and chemicals you are exposed to and what effects this might have on your children and grand-children...).


How do you detect epigenetic tags on a DNA sequence? One method is to treat the DNA with bisulfite first before amplifying and sequencing it. Bisulfite converts cytosine to what ends up appearing as a thymine (a C (to a U) to a T in the DNA sequence) but it does not affect cytosines with a methyl group that is attached. (To be clear there are more types of epigenetic "tags" then methylated cytosine, and not all types of epigenetics modify DNA nucleotides; this is just one type.)  So, you can compare bisulfite treated and non-treated DNA sequences and work out if there is a difference in epigenetic modifications.


Okay, bear with me. Recently the giraffe genome was reported in a comparative genomics project that included its shorter necked cousin the okapi ( A number of genes with changes that likely lead to the giraffe's unique development were identified including FGF growth factors and HOX genes that guide development. Furthermore, the authors found changes in genes that are likely involved in tolerating toxins in their diet (acacia leaves for example are very toxic and contain a range of alkaloids).

Okay, you can guess where I'm going with this.  Giraffes eat food that is very biologically active and toxic to many other species...  Just for fun, are there epigenetic signals in the genes implicated to be responsible for a giraffe's long neck? Do these vary among giraffes? Are they correlated with neck size and/or diet? Does the signal transmit across generations?   (Could epigenetic potential have evolved to be sensitive to, and respond to, trees of different heights in the giraffe's (ancestor's) diet?)  It would be fairly straightforward to work the first part of this out using giraffe DNA samples and bisulfite sequencing. Giraffe's already serve as excellent examples of the process of evolution (perhaps most famously the route of the recurrent laryngeal nerve in giraffes). We now have the tools to determine if, after all of these years (centuries), there could also in fact be a Lamarckian "L'influence des circonstances" in giraffe neck length?

  • However, to say that Lamarck was at a conceptual dead end and only known for the theory of inheritance of acquired characteristics is a part of the general misunderstanding that is associated with the man. He was a French naturalist that was involved in a wide range of scientific topics. Lamarck rebelled against the predominant thought of uniformitarianism in nature at the time. His idea around 1800 that some aspects of nature were mutable and could change was revolutionary and formed part of the foundation for Darwin's theory of natural selection and other components of the theory of evolution.

Further reading

Agaba, M., Ishengoma, E., Miller, W. C., McGrath, B. C., Hudson, C. N., Reina, O. C. B., ... & Praul, C. A. (2016). Giraffe genome sequence reveals clues to its unique morphology and physiology. Nature Communications, 7.
Feil, R., & Fraga, M. F. (2012). Epigenetics and the environment: emerging patterns and implications. Nature Reviews Genetics, 13(2), 97-109.
Gillispie, C. C. (1958). Lamarck and Darwin in the History of Science. American Scientist, 46(4), 388-409.

Red pigment in birds: a role in speciation?

There are various hypotheses about the role of behavior and speciation. One of these is the evolution of mate choice, where a genetic variant results in a phenotype that potential mates respond to, and the response is also under genetic control. This requires the simultaneous evolution of at least two loci (the signal and the behavioral response) and a problem with this line of reasoning is that the alleles at the two genes can quickly recombine away from each other unless they are genetically close together along a chromosome (and/or recombination is suppressed by a chromosomal rearrangement). Another theory is the "good genes" hypothesis. That an individual with advantageous alleles can also signal this phenotypically and mates will choose these individuals (a cool example of this is meiotic drive suppression in stalk eyed flies).

This is interesting. Two studies just came out, one in the zebra finch ( and another study in the canary (, and found that the gene responsible for variation in red pigment in the beak and feathers is due to expression levels of CYP2J19. Interestingly, this pigment is also used in the retinas to screen certain colors of light. And, it is expressed in the liver. Many of the CYP family (a.k.a. the Cytochrome P450 family) of genes are involved in detoxification of a range of compounds.

This is purely speculative, I have not had time to investigate what is known about CYP2J19's precise functions, but what if CYP2J19 in birds acted simultaneously as a mate choice signal (beaks and feather pigment) and a component in the behavioral response (retina pigment/light sensitivity filter) and maybe also had a "good genes" role as well (liver detoxification)?  (See also the "green-beard effect" which CYP2J19 variation may also be a candidate for.)

Regardless, this should be followed up in other groups of birds. There are rapid speciation events associated with transitions between red and yellow plumage and a comparative study of DNA variation at CYP2J19 in groups like the Hawaiian honeycreepers might be enlightening.

High-res image. Image: Douglas Pratt, in Conservation Biology of Hawaiian Forest Birds, Yale University Press" (Tiff version available,

The evolution of antibiotic resistance

Here is one result from this semseter's genetics teaching lab that I wanted to share. The students grew bacteria on a series of gradient media that had increasing concentrations of an antibiotic. At the end of the experiment the bacteria could grow on levels of antibiotic that would have prevented growth before the experiement (which we tested with a control that was genetically identical at the beginning of the experiment and was not exposed to antibiotics). The sucessive generations of bacteria evolved by mutations and selection to tolerate the antibiotic. (One of the goals of this was to show the students an example of evolution in action and illustrate the risks of over-using antibiotics.) We then measuered levels of gene expression for all the genes in the genome and identified which genes had increased their acitvity and which ones had decreased acitivity to allow them to survive (by extracting RNA and hybridizing it to an Affymetrix "GeneChip E. coli Genome 2.0 Array"). Next year I'm planning to have the students sequence some of the genes involved and try to find the precise mutations that have changed gene expression levels.