'Junk DNA' could play an important role in diabetes

Researchers at Imperial College London have found that so-called 'junk DNA' could play a role in diabetes.

The human genome is enormous, containing billions of ‘letters’ of genetic code. But among the thousands of genes which code for vital proteins, hidden in plain sight are much vaster chunks of non-coding junk DNA, previously thought to have no function.

Shining the spotlight on these dark, unexplored regions of the genome, an international team led by scientists at Imperial has found that some of this junk DNA has an important regulatory function in the pancreas.

The findings, published this month in the journal Cell Metabolism, reveal that specific non-protein coding regions regulate key genes in beta cells – the insulin-producing cells of the pancreas which help to balance blood sugar in the body.

“There’s only a tiny proportion of the genome that codes for proteins. The rest of it was largely uncharted until a few years ago,” explained Professor Jorge Ferrer, Head of Epigenetics and Disease at the Department of Medicine at Imperial, who led the study. “But this non-coding DNA is now known to harbour many functional elements which regulate other genes.”

Earlier research by Professor Ferrer and colleagues discovered that in pancreatic cells, long regions of junk DNA are copied to RNA. Typically, RNA strands are shuttled off around the cell, carrying the instructions for making proteins. More recent studies, however, show that some RNAs that do not code for proteins are used to fine tune gene activity. But in the beta cells the function of these non-coding RNAs wasn’t clear.

ROLE FOR JUNK DNA

Now, working with researchers in the US, Spain, Italy, France and Switzerland, Professor Ferrer’s team has found what these long non-coding RNAs get up to inside the cells – they regulate key controlling genes by causing the DNA to twist and kink.

Using cell cultures and tissue samples from patients with type 2 diabetes, the team analysed the activity of genes within beta cells.

One junk region in particular, called PLUTO (PDX1 Locus Upstream Transcript), was found next door to an important controlling gene (or transcription factor) called PDX1, which helps beta cells to mature and produce insulin.

The researchers found that PLUTO changed how the DNA around it folded. These structural changes include the region around PDX1, so enhancing the activity of this key controlling gene and having knock-on effects for the beta cells.

“We know that these transcription factors are actually very important for human diabetes,” said Professor Ferrer, explaining that many people with the condition may have mutated or high risk copies of the genes.

“PDX1 is essential to countering the body’s growing resistance to insulin, so these genes are really important in terms of human diabetes – both inherited and acquired,” said Professor Ferrer.

Analysis of tissue samples revealed that both PDX1 and PLUTO were less active in the beta cells of those with type 2 diabetes. This, the researchers say, hints that non-coding regions such as PLUTO play a regulatory role in healthy cells.

The findings add weight to the idea that some of these lesser known regions of the genome, previously labelled as ‘junk‘, are in fact functional and could even play a role in the development of the condition.

Rather than just ‘noise’ caused by the cellular machinery transcribing junk code, these non-coding RNAs may subtly change the activity of key genes within beta cells and could even provide new targets for drug treatment.

Professor Ferrer added: “These long non-coding RNAs are a new class of genes whose function we can now try to unravel. They could potentially be relevant to the mechanisms underlying diabetes.”

“The findings strengthen the notion that the 98% of the genome that was dismissed as largely not functional, not interesting, actually is stuffed with very interesting, functional elements that are very important for human disease.”

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‘Human pancreatic β cell lncRNAs control cell-specific regulatory networks’ by Ferrer, J et al. was published in the journal Cell Metabolism.