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

Abstract

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.

Human naïve stem cell models reveal the role of FGF in hypoblast specification in the human embryo

“…We sought to compare the in vitro differentiation path with hypoblast formation in embryo development. We took advantage of a recent high-resolution embryo single-cell UMAP embedding 4 . This integrated embedding utilises entropy sort feature weighting (cESFW) for feature selection (3012 genes).…”

“…We projected the in vitro differentiation time course onto the embryo embedding based on transcriptome similarity over the 3012 gene set 4 (Figure 2C). As expected, most naïve PSCs in PXGL position over dpf 6/7 naïve epiblast.…”

“…Pseudotime along the hypoblast branch was calculated using the Slingshot R package 39 . Gene expression values were smoothed by taking the average gene expression for each cell and its 30 most similar cells according to the 3012 highly structured genes identified by Radley et al (2023) 4 . Logistic regression curves were fit to the smoothed expression profiles versus the hypoblast pseudotime.…”

“…We took advantage of a recent high-resolution embryo single-cell UMAP embedding 4 . This integrated embedding utilises entropy sort feature weighting (cESFW) for feature selection (3012 genes).…”

“…This begins with the first lineage segregation, which sets apart the extraembryonic trophectoderm from the inner cell mass (ICM) [1][2][3] and is followed by the second lineage segregation when the ICM differentiates into naïve epiblast and hypoblast. Morphological observation, immunostaining, and recent advances in single-cell transcriptome analysis of human embryos suggest that the sequential lineage segregation model broadly stands in human [4][5][6] . The segregation of trophectoderm in human begins around day 4 after fertilisation (dpf) in the morula, followed by hypoblast lineage segregation around dpf 5/ 6 in the inner cell mass of blastocyst.…”