bioRxivGeneticsPreprint
Meiotic and mitotic aneuploidies drive arrest of in vitro fertilized human preimplantation embryos
Rajiv C. McCoyiD, Michael C. SummersiD, Abeo McCollin, Christian Simon OttoliniiD, Kamal K AhujaiD, Alan H. HandysideiD
Abstract
The high incidence of aneuploidy in early human development, arising either from errors in meiosis or postzygotic mitosis, is the primary cause of pregnancy loss, miscarriage, and still birth following natural conception as well as in vitro fertilization (IVF). Preimplantation genetic testing for aneuploidy (PGT-A) has confirmed the prevalence of meiotic and mitotic aneuploidies among blastocyst-stage IVF embryos that are candidates for transfer. However, only about half of normally fertilized embryos develop to the blastocyst stage in vitro, while the others arrest at cleavage to late morula or early blastocyst stages. To achieve a more complete view of the impacts of aneuploidy, we applied a validated method of PGT-A to a large series (n = 909) of arrested embryos and trophectoderm biopsies. We then correlated observed aneuploidies with abnormalities of the first two cleavage divisions using time lapse imaging (n = 843). The combined incidence of meiotic and mitotic aneuploidies was strongly associated with blastocyst morphological grading, with the proportion ranging from 20% to 90% for the highest to lowest grades, respectively. In contrast, the incidence of aneuploidy among arrested embryos was exceptionally high (94%), dominated by mitotic aneuploidies affecting multiple chromosomes. In turn, these mitotic aneuploidies were strongly associated with abnormal cleavage divisions, such that 51% of abnormally dividing embryos possessed mitotic aneuploidies compared to only 23% of normally dividing embryos. We conclude that the combination of meiotic and mitotic aneuploidies drives arrest of human embryos in vitro, as development increasingly relies on embryonic gene expression at the blastocyst stage.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 2
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