Integrative analysis of single-cell embryo data reveals transcriptome signatures for the human pre-implantation inner cell mass.

Wei, Xinshu; Fang, Xiang; Xiu, Yu; Liu, Hong; Guo, Yanhui; Qi, Yifei; Sun, Chuanbo; Han, Dingding; Liu, Xiaonan; Li, Na; Hu, Hao

doi:10.1016/j.ydbio.2023.07.004

Cited by 5 publications

(8 citation statements)

References 69 publications

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“…Our cell type annotations formed quantifiably more distinct clusters when using top rank genes selected by cESFW compared to the top ranked genes from conventional HVG selection. Furthermore, we observe coherent dataset integration without having to apply batch correction methods as in previous analyses (Meistermann et al 2021;Wei et al 2023). We propose that cESFW achieves good integration of datasets from different sources because improved feature selection tips the biological signal to noise ratio in favour of the biologically relevant expression profiles in the data.…”

Section: Discussionmentioning

confidence: 60%

“…More recent studies have proposed two bifurcations, but have not demonstrated separate branch point populations (Yanagida et al 2021; A. Radley et al 2023; Wei et al 2023).…”

Section: Resultsmentioning

confidence: 96%

“…These datasets have previously been characterised (Petropoulos et al 2016; Giuliano G. Stirparo et al 2018; Meistermann et al 2021; M. Singh et al 2023; Wei et al 2023), and there is a foundation of experimental knowledge defining the expected distinct cell types and stages.…”

Section: Resultsmentioning

confidence: 99%

“…However, the existence of two branch points in human embryogenesis has been questioned in previous analyses of scRNA-seq data (A. . More recent studies have proposed two bifurcations, but have not demonstrated separate branch point populations (Yanagida et al 2021;Wei et al 2023).…”

Section: Lineage Branching Blastocyst Developmentmentioning

confidence: 94%

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Branching topology of the human embryo transcriptome revealed by entropy sort feature weighting

Radley,

Smith

2023

Preprint

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Single cell transcriptomics (scRNA-seq) transforms our capacity to define cell states and reveal developmental trajectories. Resolution is challenged, however, by high dimensionality and noisy data. Analysis is therefore typically performed after sub-setting to highly variable genes (HVGs). However, existing HVG selection techniques have been found to have poor agreement with one another, and tend to be biased towards highly expressed genes. Entropy sorting provides an alternative mathematical framework for feature subset selection. Here we implement continuous entropy sort feature weighting (cESFW). On synthetic datasets, cESFW outperforms HVG selection in distinguishing cell state specific genes. We apply cESFW to six merged scRNA-seq datasets spanning human early embryo development. Without smoothing or augmenting the raw counts matrices, cESFW generates a high-resolution embedding displaying coherent developmental progression from 8-cell to post-implantation stages, delineating 15 distinct cell states. The embedding highlights sequential lineage decisions during blastocyst development while unsupervised clustering identifies branch point populations. Cells previously claimed to lack a developmental trajectory reside in the first branching region where morula differentiates into Inner Cell Mass (ICM) or Trophectoderm (TE). We quantify the relatedness of pluripotent stem cell cultures to embryo cell types and identify naïve and primed marker genes conserved across culture conditions and the human embryo. Finally, by identifying genes with specifically enriched and dynamic expression during blastocyst formation, we provide markers for staging lineage progression from morula to blastocyst. Together these analyses indicates that cESFW provides the ability to reveal gene expression dynamics in scRNA-seq data that HVG selection may can to elucidate.

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Section: Discussionmentioning

confidence: 60%

“…More recent studies have proposed two bifurcations, but have not demonstrated separate branch point populations (Yanagida et al 2021; A. Radley et al 2023; Wei et al 2023).…”

Section: Resultsmentioning

confidence: 96%

Section: Resultsmentioning

confidence: 99%

Section: Lineage Branching Blastocyst Developmentmentioning

confidence: 94%

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Branching topology of the human embryo transcriptome revealed by entropy sort feature weighting

Radley,

Smith

2023

Preprint

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“…Pseudo-time analysis was performed using Palantir 28 . Subset of each cell type of interest was reprocessed before the analysis.…”

Section: Pseudo-time and Trajectory Analysismentioning

confidence: 99%

An integrative single-cell atlas to explore the cellular and temporal specificity of neurological disorder genes during human brain development

Kim,

Lee,

Koh

et al. 2024

Preprint

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Single-cell technologies have enhanced comprehensive knowledge regarding the human brain by facilitating an extensive transcriptomic census across diverse brain regions. Nevertheless, understanding the cellular and temporal specificity of neurological disorders remains ambiguous due to the developmental variations. To address this gap, we illustrated the dynamics of disorder risk gene expressions under development by integrating multiple single-cell RNA sequencing datasets. We constructed a comprehensive single-cell atlas of developing human brains, encompassing 393,060 single cells across diverse developmental stages. Temporal analysis revealed the distinct expression patterns of disorder risk genes, including autism, highlighting their temporal regulation in different neuronal and glial lineages. We identified distinct neuronal lineages diverged across developmental stages, each exhibiting temporal-specific expression patterns of disorder genes. Lineages of non-neuronal cells determined by molecular profiles also showed temporal-specific expressions, indicating a link between cellular maturation and the risk of disorder. Furthermore, we explored the regulatory mechanisms involved in early brain development, revealing enriched patterns of fetal cell types for neuronal disorders, indicative of the prenatal stage's influence on disease determination. Our findings facilitate unbiased comparisons of cell type-disorder associations and provide insight into dynamic alterations in risk genes during development, paving the way for a deeper understanding of neurological disorders.

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Unlocking trophectoderm mysteries: In vivo and in vitro perspectives on human and mouse trophoblast fate induction

Azagury,

Buganim

2024

Developmental Cell

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Integrative analysis of single-cell embryo data reveals transcriptome signatures for the human pre-implantation inner cell mass.

Cited by 5 publications

References 69 publications

Branching topology of the human embryo transcriptome revealed by entropy sort feature weighting

Branching topology of the human embryo transcriptome revealed by entropy sort feature weighting

An integrative single-cell atlas to explore the cellular and temporal specificity of neurological disorder genes during human brain development

Unlocking trophectoderm mysteries: In vivo and in vitro perspectives on human and mouse trophoblast fate induction

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