Cited by 47Reproductive Biology and FertilityPrenatal Screening and DiagnosticsSingle-cell and spatial transcriptomics

RNA-seq as a tool for evaluating human embryo competence

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Groff, Abigail F., Resetkova, Nina, DiDomenico, Francesca, Sakkas, Denny, Penzias, Alan, Rinn, John L., Eggan, Kevin·2019·Genome Research

Abstract

The majority of embryos created through in vitro fertilization (IVF) do not implant. It seems plausible that rates of implantation would improve if we had a better understanding of molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer uses an ad hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing (RNA-seq) of embryos could yield high-dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Recent advances enabling the production of RNA-seq libraries from single cells have facilitated the application of this technique to the study of transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to embryo selection procedures by generating RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for assessing embryo competence. Specifically, we show the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype and to identify candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

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  • Groff and colleagues demonstrated that aneuploidy can be estimated based on significant variations in gene expression in the affected chromosome(s) compared to reference control samples.

    “Groff and colleagues have demonstrated that aneuploidy can be estimated based on significant variations in gene expression in the affected chromosome(s) compared to reference control samples (24).”

    From Frequent loss of heterozygosity in CRISPR-Cas9–edited early human embryos (2021) · cites this paper as [24]

    The Results section, “RNA-seq can provide a digital karyotype” (page unavailable), reports estimating potential aneuploidy from chromosome-level RNA read-count outliers. The Methods section, “RNA digital karyotype” (page unavailable), describes comparing chromosome expression with a mean across samples and testing significant deviations, not comparing affected chromosomes with designated reference control samples. (LLM, conf=0.84)

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Cited by

Sorted by citations

Authors
Groff, A. F., Resetkova, N., DiDomenico, F., Sakkas, D., Penzias, A., Rinn, J. L., & Eggan, K.
Affiliations
  • Harvard University (US)
  • Beth Israel Deaconess Medical Center (US)
  • Boston IVF (US)
Venue
Genome Research
Published
2019-09-23
Volume
29
Issue
10
Pages
1705-1718
ISSN
  • 1088-9051 (ISSN-L)
  • 1549-5469
OpenAlex
W2977229130
Cited by
47
References
4
Citations by year
2026: 3 · 2025: 7 · 2024: 8 · 2023: 12 · 2022: 8 · 2021: 5 · 2020: 4
Type
posted content
Language
en
Open access
Locations
  • Genome Research (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HighWire Press Open Archive (submittedVersion)
Funders
  • Harvard Stem Cell Institute
  • Howard Hughes Medical Institute
  • Stowers Medical Institute
  • HHMI
  • Integramed National Innovation
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Reproductive Biology and Fertility
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Prenatal Screening and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
embryo developmental competence, embryo selection, in vitro fertilization, trophectoderm biopsy, embryo transcriptome, preimplantation genetic testing for aneuploidy, embryo implantation, embryo quality assessment
MeSH terms
Exome Sequencing, Biopsy, Blastocyst, Female, Fertilization in Vitro, Genetic Testing, Humans, Karyotyping, Embryo Implantation, Pregnancy, Sequence Analysis, RNA, Preimplantation Diagnosis, Embryonic Development, Karyotype

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