A reductive evolution from a complex community of ancestors as a general trend in the evolution of life.

Meet the Pompeii Worm (Alvinella pompejana).

This little creature is famous among biologists because it is the most heat tolerant animal known to exist – it lives buried in the sides of hydrothermal vents and is thus regularly exposed to water temperatures up to 176 degrees Fahrenheit.  To survive in such an extreme environment, the worm lives in a close symbiotic relationship with thermophilic bacteria:

Scientists believe the bacteria on the worms’ backs act like firefighters’ blankets, shielding the worms from intermittent blasts of hot, metal-rich water.

http://news.nationalgeographic.com/news/2005/01/0117_050117_tubeworms.html

While this shows us another example of the way the global bacterial superorganism can facilitate the evolution and survival of other eukaryotic organisms, right now, let’s focus on the gene content of this worm, as a library of 15,858 unique cDNAs has just been described. [1]

Another Unicellular Genome

Another genome from a single-celled organism has been sequenced. This time it is the green algae, Chlorella. Chlorella are tiny algae that can reproduce quite rapidly. Yet despite the stream-lined nature of the organism, it retains most of the phytohormone biosynthesis pathways necessary to the development and growth of land plants.

Check it out:

Another interesting feature of the NC64A genome was the presence of homologs of receptors and biosynthetic enzymes of land plant hormones, such as abscisic acid, auxin, and cytokinin. The presence of these homologs does not necessarily imply the existence of plant hormones and their related functions in Chlorella but supports the hypothesis that genes involved in phytohormone biosynthesis and perception were established in ancestral organisms prior to the appearance of land plants.

Not only does this genome add more evidence to the growing plausibility of front-loading, but it also seems to offer a clue that the horizontal transfer of genetic information played a key role in the evolution of one of its key features – it’s unique chitin cell wall.

Pseudo Goes to Work

In the previous posting, I tried to help you visualize pseudogenes from a teleological perspective, demonstrating that the non-teleological perspective is not necessary.  Let’s take it a step further.

Pseudogenes are sequences of DNA that are similar to functional genes, but have acquired defects that prevent the expression of functional products. Such sequences are generated by gene duplication, where one duplicate undergoes some lesion that is not selected against. As a result, the defective gene (now a pseudogene) may continue to undergo further mutational insult, effectively causing it to decay into oblivion over time.

Yet because the cellular architecture entails that an “RNA world” exists in parallel with a “protein world,” might many of these pseudogenes simply be genes escaping the constraints of the protein world in order for the opportunity to more fully participate in the RNA world?

Pseudogenes in the Matrix

Over at BioLogos, Dennis Venema and Darrel Falk have written a nice summary of pseudogenes and how they relate to our understanding of common descent.  But we can take their discussion to a deeper level to help you better appreciate pseudogenes from a teleological perspective.

The SRP, Alu Elements, and Nudging

I’ve combined the essays about the signal recognition partcle, Alu elements, cytosine deamination, all connected by front-loading. All 11, 465 words of it.

FL Thoughts Out Loud

It’s often the case that I get an idea but don’t have the time to write up a decent blog to spell it out.  As a result, some ideas come and go.  So I will start a new tag entitled, FLE ruminations.  Here I will jot down ideas for possible future reference and/or expansion.  We’ll kick it off with some stuff that is in the process of connecting genomic shape to front-loading:

Alu Mania

I’ve been talking about Alu elements for weeks now, so I was going to try to change the topic.  But alas, I can’t stop myself.  Here is some more Alu Fun for those similarly intrigued by the manner in which these nifty reformatting devices can facilitate evolution.

First, here is a decent video that outlines the basics of Alu retrotansposition.

Second, remember how it has become clear that the genome has a three-dimensional architecture?

No rest for the SRP

Earlier in the summer, I pointed to a study that shows evidence of genome reformatting during human evolution:

In new research the Leeds team reports that a protein known as REST plays a central role in switching specific genes on and off, thereby determining how specific traits develop in offspring.

The study shows that REST controls the process by which proteins are made, following the instructions encoded in genes. It also reveals that while REST regulates a core set of genes in all vertebrates, it has also evolved to work with a greater number of genes specific to mammals, in particular in the brain – potentially playing a leading role in the evolution of our intelligence.

[…]

Says lead researcher Dr Ian Wood of the University’s Faculty of Biological Sciences: “This is the first study of the human genome to look at REST in such detail and compare the specific genes it regulates in different species. We’ve found that it works by binding to specific genetic sequences and repressing or enhancing the expression of genes associated with these sequences.

“Scientists have believed for many years that differences in the way genes are expressed into functional proteins is what differentiates one species from another and drives evolutionary change – but no-one has been able to prove it until now.”

– Here

The Shape of the Genome

The more we learn about the cell, the more and more sophisticated is becomes.  In biochemistry and molecular biology, it has long been known that shape is a crucial feature of macromolecules such as proteins and RNA – the functional, phenotypic core of the cell.  Change the shape of any particular protein or RNA and you are likely to change the function.  But it is now time to take that insight to a new level.

When it comes to the genome, we have long focused on it in linear terms – a mere sequence of nucleotides.  But thanks to some fascinating research, it is now becoming clear that we need to start thinking about the shape of the genome:

By breaking the human genome into millions of pieces and reverse-engineering their arrangement, researchers have produced the highest-resolution picture ever of the genome’s three-dimensional structure.

The picture is one of mind-blowing fractal glory, and the technique could help scientists investigate how the very shape of the genome, and not just its DNA content, affects human development and disease.

“It’s become clear that the spatial organization of chromosomes is critical for regulating the genome,” said study co-author Job Dekker, a molecular biologist at the University of Massachusetts Medical School. “This opens up new aspects of gene regulation that weren’t open to investigation before. It’s going to lead to a lot of new questions.”

[…]

By studying the pairs, the researchers could tell which genes had been near each other in the original genome. With the aid of software that cross-referenced the gene pairs with their known sequences on the genome, they assembled a digital sculpture of the genome. And what a marvelous sculpture it is.

“There’s no knots. It’s totally unentangled. It’s like an incredibly dense noodle ball, but you can pull out some of the noodles and put them back in, without disturbing the structure at all,” said Harvard University computational biologist Erez Lieberman-Aiden, also a study co-author.

In mathematical terms, the pieces of the genome are folded into something similar to a Hilbert curve, one of a family of shapes that can fill a two-dimensional space without ever overlapping — and then do the same trick in three dimensions.

How evolution arrived at this solution to the challenge of genome storage is unknown. It might be an intrinsic property of chromatin, the DNA-and-protein mix from which chromosomes are made. But whatever the origin, it’s more than mathematically elegant. The researchers also found that chromosomes have two regions, one for active genes and another for inactive genes, and the unentangled curvatures allow genes to be moved easily between them.

Lieberman-Aiden likened the configuration to the compressed rows of mechanized bookshelves found in large libraries. “They’re like stacks, side-by-side and on top of each other, with no space between them. And when the genome wants to use a bunch of genes, it opens up the stack. But not only does it open the stack, it moves it to a new section of the library,” he said.

Cellular Computation

Shapiro next turns his attention to the manner in which the genome interacts with the rest of the cell to carry out computations. He uses the classic example of the lac operon to draw out several general principles:

• Weak interactions, specific binding and cooperativity are essential aspects of molecular computations in cells.

• Repetition in DNA and proteins means that specific logical operations arise through combinations of basic circuit elements (e.g. complex regulatory regions in
• DNA, intra- and intermolecular interactions between protein domains).

• Allostery, the fact that binding of one ligand affects binding a distinct ligand, confers communication and processing capabilities on individual molecules so that cellular network nodes act as complex microprocessors.

• Layering of weak and bfuzzyQ interactions provides overall sharpness to integrated cellular responses (i.e.cells operate by Fuzzy Logic principles; Zadeh, 1975).

• Cells use chemical symbols to represent physiological information.

• No separation exists between control molecules and execution molecules, telling us we cannot apply Cartesian dualism models to the E. coli cell, or any other cell.

• Participation of DNA directly in formation of repression and transcription nucleoprotein complexes suggests that it may also not be useful to apply Turing’s concepts of separate “machine” and “tape” (Turing, 1950) to cellular computations.