Evidence map›Paper›PMID 31548358›Full record

ArticleGenome research2019

RNA-seq as a tool for evaluating human embryo competence.

Abigail F Groff, Nina Resetkova, Francesca DiDomenico, Denny Sakkas, Alan Penzias, John L Rinn, Kevin Eggan

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 50 citations in OpenAlex.

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  9. Frontiers in cell and developmental biology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Abigail F Groff *Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA.ORCID 0000-0002-7424-9410
Nina Resetkova *Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA.
Francesca DiDomenicoDepartment of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA.
Denny SakkasBoston IVF, Waltham, Massachusetts 02451, USA.
Alan PenziasBoston IVF, Waltham, Massachusetts 02451, USA.
John L RinnDepartment of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA.
Kevin EgganDepartment of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA.
Harvard University · USBeth Israel Deaconess Medical Center · USBoston IVF · US

Funding

Howard Hughes Medical Institute
6 · The paper itself

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.

Indexed as

Fertilization in VitroGenetic TestingBiopsyBlastocystEmbryo ImplantationEmbryonic DevelopmentExome SequencingFemaleHumansKaryotypeKaryotypingPregnancyPreimplantation DiagnosisSequence Analysis, RNA

Identifiers

PMID31548358
PMCPMC6771404
OpenAlexW2977229130

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.