Towards Improving Embryo Prioritization: Parallel Next Generation Sequencing of DNA and RNA from a Single Trophectoderm Biopsy View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Noga Fuchs Weizman, Brandon A. Wyse, Ran Antes, Zenon Ibarrientos, Mugundhine Sangaralingam, Gelareh Motamedi, Valeriy Kuznyetsov, Svetlana Madjunkova, Clifford L. Librach

ABSTRACT

Improved embryo prioritization is crucial in optimizing the results in assisted reproduction, especially in light of increasing utilization of elective single embryo transfers. Embryo prioritization is currently based on morphological criteria and in some cases incorporates preimplantation genetic testing for aneuploidy (PGT-A). Recent technological advances have enabled parallel genomic and transcriptomic assessment of a single cell. Adding transcriptomic analysis to PGT-A holds promise for better understanding early embryonic development and implantation, and for enhancing available embryo prioritization tools. Our aim was to develop a platform for parallel genomic and transcriptomic sequencing of a single trophectoderm (TE) biopsy, that could later be correlated with clinical outcomes. Twenty-five embryos donated for research were utilized; eight for initial development and optimization of our method, and seventeen to demonstrate clinical safety and reproducibility of this method. Our method achieved 100% concordance for ploidy status with that achieved by the classic PGT-A. All sequencing data exceeded quality control metrics. Transcriptomic sequencing data was sufficient for performing differential expression (DE) analysis. All biopsies expressed specific TE markers, further validating the accuracy of our method. Using PCA, samples clustered in euploid and aneuploid aggregates, highlighting the importance of controlling for ploidy in every transcriptomic assessment. More... »

PAGES

2853

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41598-019-39111-7

    DOI

    http://dx.doi.org/10.1038/s41598-019-39111-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112397955

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30814554


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