Multiomics and deep learning dissect regulatory syntax in human development | Nature

## Summary
Download PDF Subjects Development Epigenomics Abstract Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression 1 . Here we present the Human Development Multiomic Atlas, a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types and more than 1 million candidate cis -regulatory elements, many of which exhibit organ-specific in vivo enhancer activity. Main During human development, the diversity of cell types arises through differential expression and activity of transcription factors, which integrate cell-intrinsic and -extrinsic signals to direct gene regulation 1 . For example, whereas expression of the CUX2 marker gene was restricted to neurons, the top motif in neurons, NEUROD1 , showed increased accessibility in neurons, fibroblasts and neural crest-derived cell types, reflecting motif degeneracy and context-dependent activity of transcription factors during development.

## Article Content
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Subjects
Development
Epigenomics
Abstract
Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression
1
. Mapping accessible chromatin offers critical insights into transcriptional control, but available datasets for human development are restricted to bulk tissue, single organs or single modalities
2
. Here we present the Human Development Multiomic Atlas, a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types and more than 1 million candidate
cis
-regulatory elements, many of which exhibit organ-specific in vivo enhancer activity. Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity. We identify ‘hard’ syntactic rules requiring precise motif spacing and orientation, ‘soft’ rules allowing flexible motif arrangements, and ubiquitous motifs inhibiting accessibility. Model-based interpretation of genetic variants reveals that disruption of motifs with positive and negative effects is associated with concordant effects on gene expression. Our work delineates how motif syntax governs cell-type-specific chromatin accessibility and provides a foundational resource for decoding
cis
-regulatory logic and interpreting genetic variation during human development.
Main
During human development, the diversity of cell types arises through differential expression and activity of transcription factors, which integrate cell-intrinsic and -extrinsic signals to direct gene regulation
1
. Transcription factors bind specific sequences of DNA in
cis
-
regulatory elements, often inducing local chromatin accessibility and altering the expression of proximal genes
2
. However, we lack a comprehensive view of the transcription factor motifs that drive chromatin state changes during human development, limiting our understanding of how transcription factor binding site organization—or syntax—contributes to regulation
3
.
Mapping chromatin accessibility using DNase I hypersensitive sites sequencing (DNase-seq) and assay for transposase-accessible chromatin using sequencing (ATAC–seq)
2
,
4
has enabled inference of transcription factor activity via sequence motifs in human tissues
5
,
6
. However, bulk measurements obscure cellular heterogeneity, and most single-cell atlases have focused on individual organs
7
,
8
or single omic modalities
9
,
10
. A multi-organ, multi-modal view is needed to capture the cell context specificity of
cis
-regulation and link chromatin state to transcriptional programs.
Chromatin accessibility often arises from cooperative transcription factor binding, either through direct interactions between transcription factors
11
,
12
or through competition with nucleosomes
13
,
14
,
15
. These mechanisms respectively impose either hard (fixed) or soft (flexible) constraints on motif syntax. Yet the generality of such rules across human development is largely unknown. Furthermore, complex disease-associated genetic variants are enriched in the non-coding genome
16
, but our ability to predict the variants that disrupt regulatory activity in specific cell types remains limited.
Recent deep learning models trained to predict base-resolution chromatin accessibility profiles from local DNA sequence learn causal sequence features that influence accessibility
17
,
18
,
19
. Beyond de novo discovery of predictive motifs and transcription factor footprints, these models enable in silico interrogation of regulatory sequence syntax and non-coding genetic variants by predicting the quantitative effects of DNA sequence changes on accessibility
17
,
20
. Thus, deep learning models provide a powerful framework for decoding the logic of how transcription factor binding influences chromatin accessibility and linking sequence variation to disruption of
cis
-regulation.
Here, we present the Human Development Multiomic Atlas (HDMA), a multiomic, multi-organ single-cell atlas that profiles chromatin accessibility and gene expression in 12 human fetal organs. We mapped more than one million accessible regulatory elements, and demonstrated their ability to resolve organ-specific and cell-type-specific enhancer activity in vivo. We trained and interpreted deep learning models to predict cell-type-resolved accessibility, defined a lexicon of regulatory sequence motifs driving accessibility, and inferred predictive motif instances across the genome per cell type. Interrogation of motif syntax uncovered both hard and soft syntactic constraints. Finally, we prioritized disease-associated variants that are likely to perturb regulatory function during development. HDMA provides a foundational

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## Expert Analysis

### Merits
- Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity.
- However, we lack a comprehensive view of the transcription factor motifs that drive chromatin state changes during human development, limiting our understanding of how transcription factor binding site organization—or syntax—contributes to regulation 3 .
- Cell identity was corroborated by significant transcription factor motif enrichments within cluster-specific accessible chromatin peaks (Supplementary Note 2 ).
- For VISTA enhancers annotated as active in brain, heart and eye, we observed strong enrichment of both accessibility (one-sided Wilcoxon rank-sum test, P = 10 −437 for brain, P = 10 −452 for heart and P = 9.11 × 10 −48 for eye; AUROC probability = 0.72 for brain, 0.75 for heart and 0.59 for eye) (Fig. 2f ) and gene expression (one-sided Wilcoxon rank-sum test, P = 1.04 × 10 −38 for brain, P = 1.23 × 10 −166 for heart and P = 2.77 × 10 −23 for eye; AUROC probability = 0.57 for brain, 0.67 for heart and 0.57 for eye) (Extended Data Fig. 3a ) in the HDMA cell type clusters from the corresponding organs.

### Areas for Consideration
N/A

### Implications
- Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity.
- Main During human development, the diversity of cell types arises through differential expression and activity of transcription factors, which integrate cell-intrinsic and -extrinsic signals to direct gene regulation 1 .
- However, we lack a comprehensive view of the transcription factor motifs that drive chromatin state changes during human development, limiting our understanding of how transcription factor binding site organization—or syntax—contributes to regulation 3 .
- A multi-organ, multi-modal view is needed to capture the cell context specificity of cis -regulation and link chromatin state to transcriptional programs.

### Expert Commentary
This article covers cell, accessibility, transcription topics. Notable strengths include discussion of cell. Readability: Flesch-Kincaid grade 0.0. Word count: 2187.