The Race Is On to Find Roles for Genetic "Junk"

Evolution News & ViewsEvolution News & Views April 29, 2013 5:18 AM | Permalink

The story coming out of a UC San Francisco lab is not just that scientists have discovered a new function for specific DNA in mice previously considered to be junk. It’s much more profound than that:

Their discovery in mice is likely to further fuel a recent scramble by researchers to identify roles for long-neglected bits of DNA within the genomes of mice and humans alike. (Emphasis added.)

This represents a sea change in thinking about DNA. In the past, why would anyone care about studying useless leftovers of evolution?

While researchers have been busy exploring the roles of proteins encoded by the genes identified in various genome projects, most DNA is not in genes. This so-called junk DNA has largely been pushed aside and neglected in the wake of genomic gene discoveries, the UCSF scientists said.

But if those snippets of non-coding DNA actually have important functional roles, they might help us understand cells and find new ways to attack disease.

Brain Code

The DNA studied at UCSF produces transcripts called long non-coding RNA, or lncRNA for short. The lncRNAs, unlike messenger RNAs, do not produce proteins, even though they are transcribed in the same way; “they, too, consist of unique sequences of nucleic acid building blocks.” In other words, they are complex; if they have a role, they are also specified, satisfying two criteria for intelligent design.

Evidence indicates that lncRNAs can tether structural proteins to the DNA-containing chromosomes, and in so doing indirectly affect gene activation and cellular physiology without altering the genetic code. In other words, within the cell, lncRNA molecules act “epigenetically” — beyond genes — not through changes in DNA.

Their work on just 2,000 out 9,000 such transcripts generated so much data, it will take several labs to identify all the functional roles. So far, they know that many of these lncRNAs are associated with different cell types in the brain. Understanding how they work, or how they fail, could lead to interventions for devastating conditions like Huntington’s Disease.

Specified Complexity Squared

Meanwhile across the Atlantic, Europeans have found that even coding genes have multiple tricks up their sleeves. News from the European Molecular Biology Laboratory (EMBL) “pushes the boundaries of transcription”: i.e., there’s far more functional potential in those genes than previously thought. In a nutshell:

  • A new technique reveals that each gene can be transcribed into many messenger RNAs with different start- and end-points
  • The sheer extent of boundary diversity challenges the traditional view of transcription
  • The technology and data provide a new way to evaluate the functional range of genes

What could be more intelligently designed than an orchestra? They don’t say that, but they imply it:

Like musicians in an orchestra who have the same musical score but start and finish playing at different intervals, cells with the same genes start and finish transcribing them at different points in the genome.

Well, if orchestra players picked their charts at random from the score, and played them at random times, it wouldn’t make musical sense, would it? The analogy implies that there are higher levels of control for gene transcripts so that they play their parts correctly. Consider the “score” for a humble yeast cell:

Hundreds of thousands of unique mRNA transcripts are generated from a genome of only about 8000 genes, even with the same genome sequence and environmental condition. “We knew that transcription could lead to a certain amount of diversity, but we were not expecting it to be so vast,” explains Lars Steinmetz, who led the project.

Yeast was supposed to be a simple model for the “one gene — one mRNA” hypothesis. The EMBL researchers found, instead, that yeast genes can each generate “dozens or even hundreds of unique mRNA molecules, each with different boundaries.” Why would this be?

This suggests that not only transcript abundance, but also transcript boundaries should be considered when assessing gene function. Altering the boundaries of mRNA molecules can affect how long they stay intact, cause them to produce different proteins, or direct them or their protein products to different locations, which can have a profound biological impact. Diversifying mRNA transcript boundaries within a group of cells, therefore, could equip them to adapt to different external challenges.

Identifying this diversity is just a first step. From there, design thinking can lead to further understanding, they imply: “Now that we are aware of how much diversity there is, we can start to figure out what factors control it.”

The Epigenetics Revolution

Awareness of epigenetic factors has expanded the universe of genomics in profound ways, as these two articles illustrate. Epigenetics not only expands the specified complexity of the genome, but also theories of inheritance. Last month Nature discussed new findings about the heritability of one class of epigenetic factors, methylation marks:

These methylation classes differ in their mechanisms of establishment, maintenance and inheritance; and they have distinct roles in genomic regulation, thereby leading to differing effects on the characteristics — or phenotype — of an organism.

Where is this extra layer of control stored? It’s not clear if the “epigenome” is something contained within the genome, or if it is somewhere in the background that creates an “additional level of heritable information” in the organism. If the latter, biologists may have to coin new terms like “epialleles”:

A high epiallelle frequency in a closely related population, as a result of inheritance and/or recurrent mutation, may explain phenotypic variation. In this case, an assessment of epigenetic information could add to our understanding of the heritable components that lead to an individual’s traits. Early indications from inbred populations of A. thaliana, called synthetic epigenetic recombinant inbred lines, suggest this may be true. However, genetic variation may control the rate of formation of epialleles, returning us to the question of which form of variation is the causal level of control.As in most cases, the reality is more complicated than either of the two possibilities alone. Epigenetic information seems to associate with the genetic content of an individual in a variety of ways, which means that we still do not know how often epigenetic states are associated with phenotypic variation.

Information; control; these are words familiar from design thinking. Darwinian evolution, when it’s even mentioned, is only peripheral to such research: e.g., “Our findings have implications for genome compaction, evolution and phenotypic diversity between single cells.” The implications are usually left as an exercise. Clearly, the expanding universe of specified complexity in the cell is good for intelligent design theory, but a headache for neo-Darwinism.


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