13 Non-coding variation in disease

Question 1

Why might non-coding region such as enhancers be particularly interesting when thinking about causing disease?

Answer 1

Enhancers are used in different tissues and are temporally regulated. So variants in them may only affected specific tissue types or have specific onsets.

Question 2

How can non-coding variants lead to disease?

Answer 2

By affecting transcription, miRNA, splicing, etc.

Question 3

What does the deep intronic variant c.3874-4522A>G do in cystic fibrosis?

Answer 3

It affected a cryptic splice site, so a cryptic exon is included. This leads to a frameshift, so the protein is truncated

Question 4

What does the BRCA1 c.-107A>T variant do in the 5’UTR?

Answer 4

Leads to DNA methylation so transcription is silenced.

Question 5

How would you prove that a variant has impacted transcription levels or transcript usage?

Answer 5

Do RNA sequencing and see which transcripts are abundant

Question 6

For the rare disease patients in the 100k genome project, 14% of diagnoses were what?

Answer 6

Non-coding variants. Researcher led identification.

Question 7

What did Nicky Whiffin and Ellingford do to the ACMG/AMP guidelines?

Answer 7

Edited the guidelines to work for non-coding variants. There will be revisions over time.

Question 8

How must you be careful about what non-coding regions you look at?

Answer 8

Well there will be millions of variants, so only look at known regulatory elements with a significant relationship to the gene.

Question 9

Why can diagnosing a childhood retinopathy be difficult?

Answer 9

Because over 300 genes can cause them, and many more symptoms like renal issues over develop later in life

Question 10

What’s the issue with functionally investigating a variant in GUCY2D, which is part of the phototransduction pathway

Answer 10

The clinically relevant tissue is not readily available

Question 11

What do you need to check before doing RNA seq to investigate a variant’s effect on a gene

Answer 11

Make sure that gene is expressed in teh sample type you’re using

Question 12

What’s an example of functional evidence?

Answer 12

RNA-seq data showing the variant leads to aberrant splicing

Question 13

How can we routinely check variants for functional info though, and which variants should we prioritise?

Answer 13

Splice AI can help to predict the effects