A recent study by Samantha Malka and colleagues used data from the 100,000 Genomes Project to find genetic causes of a rare eye condition in South Asian and African communities. This gene is present in the non-coding genome, highlighting the value of studying non-coding DNA and genomic data from diverse populations.

What is the non-coding genome?

The non-coding genome refers to the portion of our DNA that does not code for proteins, sometimes known as ‘junk DNA’.

Our genome carries all the genetic information we need for our bodies to produce proteins. These proteins allow us to survive, function, and grow.

Despite this, an estimated 98.5% of our genome does not code for proteins.

We call this portion ‘non-coding’, and its precise function is not entirely understood. However, we do know that parts of it are involved in regulating how our genes are expressed and maintaining the structure of our genome.

What is retinitis pigmentosa?

Retinitis pigmentosa refers to a varied group of rare genetic conditions that affect the function of cells in the eye.

These conditions can cause reduced vision, and often first appear as night blindness in childhood. This can then be followed by the loss of peripheral vision (being able to see to the side).

With retinitis pigmentosa affecting 1 in 2500 to 4000 people worldwide, it is vital that our approaches to diagnosis and treatment continue to improve.

What is whole genome sequencing?

The human genome is the complete set of genetic code present in each person. It is an end-to-end sequence of DNA that acts as an instruction manual, allowing us to survive and function.

Whole genome sequencing is a type of genetic testing that allows us to look at this entire code, all at once.

It lets researchers to look for any changes or ‘glitches’ in the instruction manual that might be causing problems, such as in rare genetic conditions like retinitis pigmentosa.

Why is whole genome sequencing helpful for retinitis pigmentosa?

Previous research on retinitis pigmentosa has focused only on genes in the portion of our genome that codes for proteins.

Panel sequencing was used to identify changes in a handful of specific, pre-selected genes known to cause the condition, instead of looking at the whole genome.

A recent study done by Samantha Malka and colleagues used whole genome sequencing to look at both the coding and non-coding genome.

By looking at the entire genome instead of just small sections, we can gain a much clearer and more complete picture of how changes in our coding and non-coding genes can affect our health.

Why is whole genome sequencing important for people of African and Asian ancestry?

For people who undergo genetic testing, people with African and Asian ancestry are significantly less likely to get diagnosed.

This is because these groups are underrepresented in genomic datasets, making it more difficult to spot patterns and understand the genetic causes of rare conditions.

As a result, people with African and Asian ancestry may be misdiagnosed or receive inconsistent care.

By using whole genome sequencing on groups of people with diverse ancestry, datasets can become more representative of the different populations of people with rare genetic conditions.

This can lead to understanding of new genes that cause conditions and improve the accuracy of diagnoses for everyone, especially those from historically underrepresented groups.

Discovering new genetic changes

Using whole genome sequencing data from the 100,000 Genomes Project, the researchers discovered 2 small genetic changes in a non-coding region of a gene called TMEM216.

This gene is responsible for producing little hairs called cilia, which play an important role in the function of the eyes.

The researchers discovered 2 genetic changes which affect how the TMEM216 gene is expressed in the eye.

People with these changes do not produce enough of a specific protein, leading to less cilia being produced. This results in the death of cells in the eye.

This study found 74 people with African and South Asian ancestry who had these genetic changes present in their TMEM216 gene. This shows how important it is that diverse data is included in genomic datasets to allow for new discoveries in what can cause rare genetic conditions.

Genomic data in healthcare

These findings highlight how analysing large sets of genomic data, such as from the 100,000 Genomes Project, can greatly improve our understanding of rare genetic conditions and the non-coding genome.

This is particularly important for underrepresented groups such as people with South Asian and African Ancestry. This can lead to more accurate diagnosis and development of new treatments for a more diverse range of people.

The research and its findings would not have been possible without participants from the 100,000 Genomes Project consenting to donate their data for research purposes, which Genomics England thanks them for.