rationalskepticism.org

GenesForLife wrote:It's basically like he's pointed to loads of interesting epigenetic phenomena, which are interesting enough as they are, but I don't really see where he's going with this. It appears to be a statement of "Genes alone cannot explain development/physiology, ergo there is something else co-ordinating everything, including genes". At the moment he's trying to pin chromatin biology as the source of everything else, including gene expression.

Genes provide the basic instructions for what we look like, our personalities, and what diseases we may develop. However, genes alone cannot explain how our body and our organs develop, nor all aspects of inheritance or why diseases arise.

Clearly, genes alone can't explain the complexity, diversity, and development of life on Earth, so what do they mean?

"After the mapping of the human genome, it became clear that genes alone cannot explain the complexity of life. Genes need to be turned on or off in a specific order, to enable development of the 200 cell types in our body and to sustain their normal function throughout life. We have developed a new technology, which we can use to gain insight into how cellular memory is maintained when cells divide," says Anja Groth.

Genes alone cannot explain the vast differences in complexity among worms, mice, monkeys and humans, all of which have roughly the same amount of genetic material. Scientists have found that these differences arise in part from the dynamic regulation of gene expression rather than the genes themselves. Epigenetics, a relatively young and very hot field in biology, is the study of nongenetic factors that manage this regulation...

The discovery of a new nucleotide may make biologists rethink their approaches to investigating DNA methylation. Ironically, the latest addition to the DNA vocabulary was found by chance during investigations of the level of 5-methylcytosine in the very large nuclei of Purkinje cells, says Skirmantas Kriaucionis, a postdoctoral associate in the Heintz lab, who did the research. "We didn't go looking for this modification," he says. "We just found it."

Chromosomes and their genes are arranged in a specific way throughout the nucleus, and because the nucleotide sequence of a genome alone cannot explain the functions of its genes, researchers have started investigating how the spatial organization of genes might affect how they work.

“Conceptually, we’re entering a new era,” says study author Giacomo Cavalli, of the Institute of Human Genetics in Montpellier, France. “Forty years ago we looked at single genes, now we know we need to look at them in context — that’s the 3D folding of chromosomes.

Neuroscientists posit that all of our hopes, desires, beliefs and experiences are encoded in the brain as patterns of neural firings. Just how this happens is not precisely understood, as the author attests, but we have made great strides in understanding how neurons communicate with one another. Progress has also been made in mapping which brain systems control which kinds of operations (my own field of research): One system is responsible for lifting your foot, another senses the pain when you stub your toe; one system helps you to solve arithmetic problems, another enjoys "La Bohème." A new approach to studying brains and individual differences involves making maps of how neurons connect to one another. Following the term genome, these are called connectomes.

"Why study connectomes if genomics is already so powerful?" Mr. Seung asks. "The answer is simple: Genes alone cannot explain how your brain got to be the way it is. As you lay nestled in your mother's womb, you already possessed your genome but not yet the memory of your first kiss."

Please cite this article in press as: Levin, M., Morphogenetic fields in embryogenesis, regeneration, and cancer: Non-local control of complex patterning. BioSystems (2012), http://dx.doi.org/10.1016/j.biosystems.2012.04.005

The geometric shape of the substrate upon which cells reside has crucial implications for their future behavior (Chen et al., 1997, 1998; Huang and Ingber, 2000); this geometry is an ideal example of a signal that cannot be described by genetic or proteomic profiling alone. Additional physical properties that can serve similar functions include mechanical properties of tissues (Beloussov, 2008; Beloussov and Grabovsky, 2007; Beloussov and Lakirev, 1991; Beloussov et al., 2000, 1997; Brodland et al., 1994; Discher et al., 2005; Savic et al., 1986), ultraweak photon emission (Beloussov, 2001; Popp, 2003), and bioelectrical gradients (Levin, 2007b, 2009, 2011a, 2012).

Thus, a line of such 2-headed animals could be maintained, which would be identical in DNA sequence to the normal 1-headed worms and yet have radically different behavior and body-plan architecture. The evolutionary implications of this are apparent, and demonstrate that the biophysical, epigenetic aspects of patterning may play an important role in evolution, as selection operates on animal morphologies. Thus, it is likely that a full understanding of the morphogenetic field and its informational content will need to involve cracking the bioelectric code (the mapping between spatiotemporal ionic profile patterns and tissue morphology outcomes).

Importantly however, large-scale morphostasis does not simply depend on recapitulating fixed developmental programs (Voskoboynik et al., 2007). For example, the tadpole face is quite different from that of a frog; during metamorphosis, a series of deformations must be executed and various organs and tissues displaced towards their appropriate locations. Remarkably, when developmental defects were induced in the tadpole (by manipulating the embryonic voltage gradients that guide craniofacial patterning), subsequent development was able to adjust accordingly (Vandenberg et al., 2012). Most organs were still placed into the right final positions, using movements quite unlike the normal events of metamorphosis, showing that what is encoded is not a hardwired set of tissue movements but rather a flexible, dynamic program that is able to recognize deviations, perform appropriate actions to minimize those deviations, and stop rearranging at the right time. Even the highly-mosaic C. elegans embryo can re-route cells through far-ranging movements (Schnabel et al., 2006) to counteract experimental perturbations.

Target morphology models are eschewed in biology today, mainly because of a fear of teleology (Ruse, 1989; Teufel, 2011) harkening back to the early days of preformationism, and because the field has made such progress by focusing on the difficult problem of cellular-level controls. However, there are data that suggest that prepattern models should be considered...

One set of results that suggests a target morphology model is the trophic memory in deer antlers discussed above. If there is a target morphology for the rack shape encoded directly in some way, it is easy to see how changes of that shape can be long-lived. An injury to a specific place on one tine may induce a physical change in the map structure at the corresponding location (e.g., a change in a neural network storing the morphology), causing the extra tine to be reca-pitulated in subsequent years as the antlers grow and cells “consult” (are controlled by) the map. In contrast, an emergent model views the antler rack shape as the result of purely local decisions made by cells during their growth period. The question this system would have to solve is: how to modify the rules of cell growth to result in exactly the same rack shape plus one extra tine at the specified loca-tion? This is an excellent example of an inverse problem (Fig. 3C), and is in general computationally intractable—there is no way for the system to know how the cell behavior rule set is to be modified to result in the desired pattern. This seems to be a situation in which a map model would be preferable, and indeed a priori, the emergent model wrongly predicts that such a phenomenon should not exist.

A digestive enzyme called salivary amylase plays a key role in breaking down starch into simple sugars so it can be absorbed in the gut. Humans have much higher levels of amylase in their saliva than chimpanzees, and recently it was discovered how this came about.

While chimps have only two copies of the salivary amylase gene (one on each of the relevant pair), humans have an average of six, with some people having as many as 15 (Nature Genetics, Vol 39, p1256). DNA copying errors during the production of sperm and eggs must have led to the gene being repeatedly duplicated.

To find out when the duplications happened, the gene was sequenced in people from several countries, as well as in chimps and bonobos, "We were so hoping to find a signature of selection about 2 million years ago, " says Nathaniel Dominy, a biological anthropologist now at Dartmouth College in Hanover, New Hampshire, who led the work. That is around the time our brains underwent significant growth , and one theory is that it was fuelled by a switch to a starchier diet.

But the team found the gene duplications had happened more recently-some time between 100 000 years ago and the present day. The biggest change i that period was the dawn of agriculture, so Dominy thinks the duplications happened when we started farming cereals. "Agriculture was a signal event in human evolution ," he says. "We think amylase contributed to it."

It was the advent of agriculture that allowed us to live in large settlements, which led to innovation, the cultural explosion and, ultimately, modern life. If we consider all the mutations that led to these pivotal point in our evolution, human origins begin to look like a trail of unfeasible coincidences. But that is only because we do not see the harmful mutatios that were weeded out, points out John Hawks at the University of Wisconsin-Madison. "What we're left with is the ones that were advantageous." It is only from today's viewpoint that the mutations that give us our current physical form appear to be the "right" ones to have. "It's hindsight," says Hawks. "When we look back at the whole process, it looks like a stunning series of accidents."

Although it is possible that lower AMY1 gene copy numbers have been favored by selection in low-starch populations, such an interpretation is less plausible for the simple reason that excessive amylase production is unlikely to have a significant negative effect on fitness.