sciencehabit shares a report from Science.org: A California company says it can decipher almost all the DNA code of a days-old embryo created through in vitro fertilization (IVF) — a challenging feat because of the tiny volume of genetic material available for analysis. The advance depends on fully sequencing both parents’ DNA and “reconstructing” an embryo’s genome with the help of those data. And the company suggests it could make it possible to forecast risk for common diseases that develop decades down the line. Currently, such genetic risk prediction is being tested in adults, and sometimes offered clinically. The idea of applying it to IVF embryos has generated intense scientific and ethical controversy. But that hasn’t stopped the technology from galloping ahead.
Predicting a person’s chance of a specific illness by blending this genetic variability into what’s called a “polygenic risk score” remains under study in adults, in part because our understanding of how gene variants come together to drive or protect against disease remains a work in progress. In embryos it’s even harder to prove a risk score’s accuracy, researchers say. The new work on polygenic risk scores for IVF embryos is “exploratory research,” says Premal Shah, CEO of MyOme, the company reporting the results. Today in Nature Medicine, the MyOme team, led by company co-founders and scientists Matthew Rabinowitz and Akash Kumar, along with colleagues elsewhere, describe creating such scores by first sequencing the genomes of 10 pairs of parents who had already undergone IVF and had babies. The researchers then used data collected during the IVF process: The couples’ embryos, 110 in all, had undergone limited genetic testing at that time, a sort of spot sequencing of cells, called microarray measurements. Such analysis can test for an abnormal number of chromosomes, certain genetic diseases, and rearrangements of large chunks of DNA, and it has become an increasingly common part of IVF treatment in the United States. By combining these patchy embryo data with the more complete parental genome sequences, and applying statistical and population genomics techniques, the researchers could account for the gene shuffling that occurs during reproduction and calculate which chromosomes each parent had passed down to each embryo. In this way, they could predict much of that embryo’s DNA.
The researchers had a handy way to see whether their reconstruction was accurate: Check the couples’ babies. They collected cheek swab samples from the babies and sequenced their full genome, just as they’d done with the parents. They then compared that “true sequence” with the reconstructed genome for the embryo from which the child originated. The comparison revealed, essentially, a match: For a 3-day-old embryo, at least 96% of the reconstructed genome aligned with the inherited gene variants in the corresponding baby; for a 5-day-old embryo, it was at least 98%. (Because much of the human genome is the same across all people, the researchers focused on the DNA variability that made the parents, and their babies, unique.) Once they had reconstructed embryo genomes in hand, the researchers turned to published data from large genomic studies of adults with or without common chronic diseases and the polygenic risk score models that were derived from that information. Then, MyOme applied those models to the embryos, crunching polygenic risk scores for 12 diseases, including breast cancer, coronary artery disease, and type 2 diabetes. The team also experimented with combining the reconstructed embryo sequence of single genes, such as BRCA1 and BRCA2, that are known to dramatically raise risk of certain diseases, with an embryo’s polygenic risk scores for that condition — in this case, breast cancer.
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