Mapping mutations at scale in a single gene reveals new neurodevelopmental condition

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A really interesting article and technique described in an article by the Crick which makes me wonder about this approach being used to help understand what is going on in ME/CFS.

Geneticists have uncovered a previously hidden neurodevelopmental condition, showing how variations in a single gene can give rise to distinct disorders and deepening understanding of their biological roots

The ability of different genetic variants – changes to one or more building blocks of DNA – to cause disease, and to what extent, has historically been opaque.

Geneticist and Crick group leader Greg Findlay has pioneered a new method in the hope of changing this. Called ‘saturation genome editing’, the new technique involves mapping every single variant in a given gene to work out what it does and pinpoint which changes are responsible for specific disorders.

and on non-coding variants

Joachim De Jonghe, a former postdoc in Greg’s team, had the mammoth task of testing all the single-nucleotide variants (changes to just one DNA base at a time) in RNU4-2, described in a study published in Nature today. “With a non-coding gene, there isn’t a strict DNA code to protein relationship; their functions are much less defined and studied,” says Joachim. “So, it is much harder to use current predictive tools to understand if a mutation has a detrimental effect.”

 

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I actually came across this via a new usage of the technique in an article and paper published today

Mutations in the BRCA1 gene, which normally helps to repair damaged DNA, can increase the risk of breast and ovarian cancer. Despite it being one of the most well-known and well-tested cancer risk genes, some mutations in BRCA1 lack clear evidence about their significance for cancer risk.

In research published today in Nature Genetics, Greg and team turned their attention to BRCA1. Though specific BRCA1 regions had been analysed with saturation genome editing before, a technical update to the method, developed by former PhD student in the lab, Phoebe Dace, gave the team several new insights.