These powerful tools reveal the 'control knobs' of the genome

"Whenever we sequence a human individual, we get about 3.5 million variants, and only 0.6% of those will be in coding regions. That fraction is relatively easy to interpret, Ahituv says, but for the rest, "we really don't understand what it's doing - we don't have a regulatory code"."

"Scientists are fluent in the three-nucleotide codons that make up the protein-coding genes in DNA, but these represent only about 2% of the genomic text. The remainder is written in an entirely distinct language, which researchers are yet to untangle."

"To do so, they have turned to a suite of methods known as massively parallel reporter assays (MPRAs). These tools measure how millions of isolated genetic elements or sequence variants influence the expression of a hand-picked 'reporter' gene. That helps researchers to identify the genome's control knobs and untangle their function without being overwhelmed by all the other parts of the genome."

""It's reducing it down to this synthetic system," says Ryan Tewhey, a geneticist at the Jackson Laboratory in Bar Harbor, Maine. "But you're still maintaining enough complexity to probe [genomic] space that we don't fully understand, and that's kind of the sweet spot.""

Protein-coding genes occupy only a small fraction of genomic sequence, with the rest forming a distinct, not-yet-fully-understood regulatory language. Sequencing a human individual yields millions of variants, but only a small percentage fall within coding regions that are relatively interpretable. The remaining variants are difficult to interpret because their function depends on regulatory elements rather than a clear code. Researchers are using massively parallel reporter assays to test millions of genetic elements at once by measuring how variants affect expression of a chosen reporter gene. These assays reduce complexity while preserving enough genomic space to probe regulatory function. Results can support understanding disease genetics, evolutionary changes, and development of next-generation therapeutics and AI-guided genetic circuit design.

Read at Nature