A pair of twentieth century oracles examined.

Conservation of information v. Materialism.

The echo chamber fights back?

Education or Obfuscation? Avida in Science Class
Sarah Chaffee

What is a mark of a great teacher? One is the ability to take complex subject matter and explain it in a way that your audience can relate to. The opposite would be confusing students with high-tech equipment — for example, a computer program that supposedly demonstrates evolution.

A  paper in The American Biology Teacher this month recommends a student version of the program Avida for classrooms, Avida-ED. The authors note:

[I]t can be difficult to engage students in authentic scientific practice around the topic of evolution, mainly because biological evolution can be difficult to observe. An option that overcomes limitations posed by biological model organisms is digital evolution. Populations of digital organisms — mini-programs similar to computer viruses capable of self-replication — evolve in minutes and can produce large quantities of data in a short time. An example of digital evolution software is Avida, a research platform that was developed to model and test hypotheses about evolutionary mechanisms in a highly controlled and fast system. Avida allows biologists to investigate evolutionary questions that are difficult or impossible to test in organic systems (Adami, 2006), and has been used as a model system in well over a hundred experimental evolution studies for many kinds of evolutionary hypotheses (e.g., Clune et al., 2010; Grabowski etal., 2013).

So the idea is that Avida speeds up speciation. The paper goes on:

Software that simulates evolution is available for educators (e.g., SimBio’s EvoBeaker), but Avida goes further in allowing teachers to incorporate authentic research experiences on evolution in the classroom. Chief among the many advantages of using Avida to study evolutionary processes is that it constitutes a true instance of evolution rather than a simulation of it (Pennock, 2007b). We will not repeat the argument here, but the key point is that Avida implements the causal mechanisms of evolution, producing outcomes that are not predetermined but can be studied experimentally. Digital organisms in Avida (aka “Avidians”) replicate, mutate, and compete with other organisms for resources in their computational environment (Fig. 1). The system possesses all of the requirements necessary for evolution by natural selection to occur (Dennett, 1995). This is why it is especially useful to evolutionary biologists for basic research, but it is also compelling to teachers who want their students to actually observe evolutionary change in the classroom in real time. 

Let’s see here. A “true instance of evolution,” without true organisms. A computer simulation is not a “simulation.” Students can “actually observe evolutionary change in the classroom.”

Strong statements! But perhaps inaccurate? Yes, way off the mark.

Is it true that the program “implements the causal mechanisms of evolution, producing outcomes that are not predetermined but can be studied experimentally”? Of course not. In their recent book Introduction to Evolutionary Informatics, Robert Marks, William Dembski, and Winston Ewert, of the Evolutionary Informatics Lab, offer a more sober perspective.

On evolutionary simulations (Avida and others):

When software engineers perform a computer search, they are always looking for ways to improve the results of the search and how to better incorporate knowledge about the program being solved into the search algorithm. Evolution computer programs written by Darwinists, on the other hand, are aimed at demonstrating the Darwinian evolutionary process. The efficiency of the search is of secondary importance.

Despite these differences, the fundamentals of evolutionary models offered by Darwinists and those used by engineers and computer scientists are the same. There is always a teleological goal imposed by an omnipotent programmer, a fitness associated with the goal, a source of active information (e.g. an oracle), and stochastic updates.

On Avida in particular:

Avida is a computer program which, its creators say, “show[s] how complex functions can originate by random mutation and natural selection.” …[C]ontrary to the claims of the authors, the source of the success of Avida is not due to the evolutionary algorithm, but to sources of information embedded in the computer program. A strong contribution to the success of Avida is [a] stairstep information source embedded in the computer program….[T]he sources of information can be mined more efficiently using other search algorithms.

At the Evolutionary Informatics Lab website, you can try out an Avida-like program, Minivida, and test for yourself how preprogramed information affects outcomes.

It’s time for a bit of honesty in evolution education! Avida shows that evolutionary processes require intelligent design to hit predetermined targets. That’s the candid takeaway from a lesson about this software. Since we don’t recommend trying to bring ID into public school classrooms, there are undoubtedly more effective uses of class time than playing with Avida-ED.

Breaking out of the echo chamber.

Toward Self-Scrutiny in Science
Sarah Chaffee

An article at Phys.org recognizes a problem in science that we know a bit about. It shows up often in the evolution controversy: lack of self-scrutiny. In his article, “On unconscious bias in science,” Dr. Jaboury Ghazoul of the Swiss Federal Institute of Technology in Zurich, describes issues in his own field, environmental science.

He notes the tendency of science towards “‘shoehorning’ observations to fit the theory.” This, he states, is a weakness of the system and not due to fraudulent behavior. Then, he writes:

None of this matters much in my field of plant ecology, beyond taxing the pride of the researchers concerned. It is more serious when derived conclusions have applied relevance, by influencing resource management or environmental policies. In applied fields of research, there is more pressure to deliver evidence, and more to be gained in doing so — which can increase the likelihood of unconscious bias. This might explain contrasting conclusions on, for example, toxicity of pesticides on bees from studies funded by corporations or environmental organisations.

This brings us to value-laden sciences such as conservation. Conservation scientists have an agenda. Our science provides an evidence base for conservation action, set within the value that global biodiversity ought to be protected. Conservation science aims to justify this value by demonstrating the benefits of biodiversity to local and global communities. But how credible can these claims be if research serves a normative conservation agenda? We are not dispassionate observers. If we question the veracity of studies funded by agrichemical industries, then shouldn’t the objectivity of research by avowed conservationists be subject to similar scrutiny?

Think about how this kind of reasoning relates to the intelligent design and evolution debate. If scientists come with the presupposition that there will be a naturalistic explanation for the origins of the universe and life, can they be “dispassionate observers”?

Some scientists have decided to speak out against those presuppositions. Those who are willing to buck the trend are a small but growing minority. Take a look at this list of 950+ scientists who dissent from Darwinian evolution.

One of them is James Tour of Rice University, who was ranked by Thomson Reuter as one of the top 10 chemists in the world, looking at citations per publication, in 2009. Tour has noted:

Those who think scientists understand the issues of prebiotic chemistry are wholly misinformed. Nobody understands them. Maybe one day we will. But that day is far from today. It would be far more helpful (and hopeful) to expose students to the massive gaps in our understanding. They may find a firmer — and possibly a radically different — scientific theory. The basis upon which we as scientists are relying is so shaky that we must openly state the situation for what it is: it is a mystery.

Let us hope that unassuming attitudes — like those of Ghazoul and Tour — will continue to impact science.

Debunking the junk DNA myth.

More Secret Codes in “Junk DNA”
Evolution News | @DiscoveryCSC

Scientists find the most interesting things when they suspect function in poorly understood parts of the genome, rather than relegating them to the junk pile as useless. Here are two recent examples.

Silent Code in Action in Actin

“Actin is an essential and abundant intracellular protein that plays a major role in developmental morphogenesis, muscle contraction, cell migration, and cellular homeostasis,” say Vedula et al. in a paper in the journal eLife. A protein this vital commands our attention. How does it perform so many different functions? What governs the destination and activity of the different forms of actin?

The paper reads like a scientific detective story. A team of researchers from the University of Pennsylvania and the National Institutes of Health wanted to know why two forms of actin (isoforms) are nearly indistinguishable in terms of their sequence (except for four amino acids at one end), but perform very different functions in the cell. They also found it intriguing that these isoforms, β-actin and γ-actin, are coded by different genes, but end up looking very similar.

Let’s divulge the conclusion in the title of the paper: “Diverse functions of homologous actin isoforms are defined by their nucleotide, rather than their amino acid sequence.” Do you hear the word “code” coming? How about “silent code”?

Here we tested the hypothesis that β- and γ-actin functions are defined by their nucleotide, rather than their amino acid sequence, using targeted editing of the mouse genome. Although previous studies have shown that disruption of β-actin gene critically impacts cell migration and mouse embryogenesis, we demonstrate here that generation of a mouse lacking β-actin protein by editing β-actin gene to encode γ-actin protein, and vice versa, does not affect cell migration and/or organism survival. Our data suggest that the essential in vivo function of β-actin is provided by the gene sequence independent of the encoded protein isoform. We propose that this regulation constitutes a global ‘silent code’ mechanism that controls the functional diversity of protein isoforms. 

Good old controlled experimentation, using the CRISPR editing tool, showed that editing the gene for one form produced working copies of the other form. Mice that had defective genes for γ-actin could be rescued by editing the β-actin gene to produce γ-actin. All they had to do was edit five nucleotides to produce healthy mice with no β-actin at all, even though previous knockout experiments showed that mice without the β-actin gene die early in development. How could this be?

Further experiments suggested that it’s not the resulting amino acid sequence that determines the function, but “silent” substitutions in the gene. Something in the β-actin gene was regulating the outcome in a different way, even though it generated only γ-actin. The γ-actin isoform went to where β-actin normally went, and performed its function as if it were β-actin.

The researchers note that different isoforms of actin can have vastly different ribosome densities, differing up to a thousand-fold. In the cytoplasm, some isoforms can compensate for other ones. This arrangement provides flexibility to the cell in most cases:

These results suggest the actin isoform with similar ribosome density can plausibly compensate for the loss of one of the isoforms. In agreement, given the orders of magnitude difference in ribosome density between β-actin and other actin isoforms, none of the other actin isoforms can compensate for the loss of β-actin. We propose that changes in ribosome density arising from silent substitutions in nucleotide sequence, affect translation dynamics and protein accumulation rates, which in turn regulate functional diversity of actins.

The authors feel this kind of “silent code” may be at work in other protein families as well. The word “code” is ubiquitous throughout this paper. In another case, they describe the targeting of one actin isoform to the cell periphery by what they call “zipcode-mediated transport.” They have more to say about coding than evolution, in fact, except in one paragraph where they invoke the common Darwinian excuse that an essential gene tends to be conserved against alteration:

Despite the fact that non-muscle actin isoform genes have evolutionarily diverged > 100  million years ago, they have retained remarkable sequence conservation, far higher than what  would be expected if the synonymous substitutions in their coding sequence were completely randomized. (Erba et al., 1986). This is consistent with our idea that actin isoform coding  sequence exists under additional evolutionary pressure, over and above the conservation of  amino acid sequence. We propose that at least some of this pressure is aimed to maintain the divergent translation dynamics within the actin family, in order to drive their divergent functions.

It appears, however, that intelligent design research could be more productive in follow-up studies. They conclude, “Further systematic analysis of knockouts of homologous isoforms would enable establishing the universality of the ‘silent code.’”

Dark Matter in Your Brain

A more appropriate term for “junk DNA” might be “dark matter” — sequences that are not yet understood. Nature News illustrates a good use of this metaphor in an article, “‘Dark matter’ DNA influences brain development.” Amy Maxmen writes, “Researchers are finally figuring out the purpose behind some genome sequences that are nearly identical across vertebrates.”

A puzzle posed by segments of ‘dark matter’ in genomes — long, winding strands of DNA with no obvious functions — has teased scientists for more than a decade. Now, a team has finally solved the riddle.

The conundrum has centred on DNA sequences that do not encode proteins, and yet remain identical across a broad range of animals. By deleting some of these ‘ultraconserved elements’, researchers have found that these sequences guide brain development by fine-tuning the expression of protein-coding genes.

There’s no reason to suspect that any of the heroes of this article doubt evolutionary theory. But one lead researcher of a new paper did what a good design scientist would do: keep looking for function until you find it.

The results, published on 18 January in Cell, validate the hypotheses of scientists who have speculated that all ultraconserved elements are vital to life — despite the fact that researchers knew very little about their functions.

“People told us we should have waited to publish until we knew what they did. Now I’m like, dude, it took 14 years to figure this out,” says Gill Bejerano, a genomicist at Stanford University in California, who described ultraconserved elements in 2004.

What they found is the opposite of evolutionary expectations, even though the article assumes evolution:

Bejerano and his colleagues originally noticed ultraconserved elements when they compared the human genome to those of mice, rats and chickens, and found 481 stretches of DNA that were incredibly similar across the species. That was surprising, because DNA mutates from generation to generation — and these animal lineages have been evolving independently for up to 200 million years.

Genes that encode proteins tend to have relatively few mutations because if those changes disrupt the corresponding protein and the animal dies before reproducing, the mutated gene isn’t passed down to offspring. On the basis of this logic, some genomicists suspected that natural selection had similarly weeded out mutations in ultraconserved regions. Even though the sequences do not encode proteins, they thought, their functions must be so vital that they cannot tolerate imperfection.

You have to wonder what function Darwinian evolution had in this research. The expectations were wrong, the results were surprising, and the team found more design than was previously known — to the point of implying perfection. The only evolution-talk sounds like an after-the-fact gloss to keep the preferred narrative from being falsified.

For more on the tortured subject of supposed trash in the genome, see The Myth of Junk DNA, by Jonathan Wells.