Discovering that one of the most widely used methods in a particular scientific field of research is fundamentally flawed can be hard news to take, but one such recent discovery has a silver lining.
The method in question, DIP-seq, is one of the most widely used methods in the study of epigenetics.
However, a team of researchers at Linköping University discovered that it was fundamentally flawed, potentially creating misleading results that could have major ramifications in an age of big data and advanced methods of DNA analysis used to study vast amounts of epigenetic data.
In a paper published to Nature Methods, however, the team led by Colm Nestor found that this error can be corrected and could potentially pave the way for dozens of breakthroughs to be discovered in old, discarded research.
While in principle every cell in our body has the same DNA sequence, different types of cells use very different types of genes, meaning additional signals are required to control which genes are used in each individual cell type.
One such signal consists of chemical groups directly attached to the DNA sequence, forming part of what is commonly called the ‘epigenetic code’. Its regulation plays an important role in normal human development but is also associated with many diseases, such as cancer.
The DIP-seq method used in epigenetic research picks out the parts of the DNA that carry an epigenetic signal using various antibodies, recognising a specific chemical structure and binding to it.
‘Pervasive errors can hide in plain sight’
However, the problem with this method was discovered when the researchers saw how the antibodies are subsequently sorted and the sequences of the DNA they have bound to are determined.
They then noticed that certain epigenetic marks always occurred in the same place, even in DNA that shouldn’t contain those epigenetic marks at all.
“Our discovery highlights the importance of experimental validation when using high-throughput technologies in research,” Nestor said.
“Without such experimental rigour, pervasive errors can hide in plain sight, concealed by their ‘consistency’ across studies.”
In terms of numbers, the team found that more than 125 existing datasets revealed DIP-seq commonly detected DNA sequences that had no epigenetic marks.
These false positives constitute 50-90pc of the detected DNA regions, and the magnitude of the effect differs between different datasets.
“Now that we know about this error, it’s extremely simple to subtract it away,” Nestor said. “Correcting for these errors will allow novel discoveries to be made from the wealth of epigenetics data already in the public domain.”
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