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

  The majority of embryos that are created through IVF do not implant. One possibility for this inefficiency is an incomplete understanding of the molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes 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 of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some 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 clinical selection procedures by generating high quality 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 use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content 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 develop a foundational dataset for identifying candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Study EGAS00001003667

• Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Dataset EGAD00010001972

• BMI EWAS summary stats

  Summary statistics for a multi-cohort epigenome-wide association study. This includes summary statistics (effect-size, standard error, p-value) for 470,000 methylation markers.

  Dataset EGAD00010001029

• An evaluation of different strategies for large-scale pooled sequencing study design.

  An evaluation of different strategies for large-scale pooled sequencing study design.

  Dataset EGAD00001000037

• Validation_for_human_early_embryonic_substitutions_

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients

  Study EGAS00001001218

• Acute myeloid leukemia sequencing data

  This study contains tumor DNA and RNA sequencing data for 1 AML patient

  Study EGAS00001006354

• Glioma sequencing data

  This study contains sequencing data for various glioma subtypes (astrocytoma, glioblastoma, diffuse midline glioma).

  Study EGAS00001006355

• Dataset for iAMP21 scRNA-seq

  10x Genomics 5' library scRNA-seq data for 4 iAMP21 patients

  Dataset EGAD00001009504

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset EGAD00001009632

• RNA-Seq for academic use only

  RNA-Seq transcriptome data is only for academic use.

  Dataset EGAD00001009675