Each of us carries in our genomes about 10 million genetic variations called single nucleotide polymorphisms (SNPs), which represent a difference of just one letter in the genetic code. Every human’s pattern of SNPs is unique and quite stable, as they are inherited from our parents and are rarely mutated, making them a kind of “natural barcode” that can identify the cells from any individual. A group of researchers from the Wyss Institute for Biologically Inspired Engineering at Harvard University and Harvard Medical School (HMS) has developed a new genetic analysis technique that harnesses these barcodes to create a faster, cheaper, and simpler way to track what happens to cells from different individuals when they are exposed to any kind of experimental condition, enabling large pools of cells from multiple people to be analyzed for personalized medicine. The research is reported in Genome Medicine.
As the Big Data revolution in healthcare gallops apace, it is becoming possible and more attractive to perform experiments on cells from multiple people simultaneously, as differences in how the cells respond can indicate that genetic variances between the individuals are conferring some kind of effect. However, keeping track of which cells belong to which person throughout
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