Engineering Papers⌕ Search
Home/Archive/DOE OSTI

DOE OSTI · 3363600

Multiomics and deep learning dissect regulatory syntax in human development

Liu, Betty B. [Stanford Univ., CA (United States)] (ORCID:0000000316557164)·Jessa, Selin [Stanford Univ., CA (United States)] (ORCID:0000000341926523)·Kim, Samuel H. [Stanford Univ., CA (United States)] (ORCID:0000000183536190)·Ng, Yan Ting [Illumina, Foster City, CA (United States); Nanyang Technological Univ. (Singapore)] (ORCID:0000000180758791)·Higashino, Soon Il [Stanford Univ., CA (United States)]·Marinov, Georgi K. [Stanford Univ., CA (United States)] (ORCID:0000000318227273)·Chen, Derek C. [Stanford Univ., CA (United States)] (ORCID:0000000196524885)·Parks, Benjamin E. [Stanford Univ., CA (United States)]·Li, Li [Stanford Univ., CA (United States)] (ORCID:0000000178866056)·Nguyen, Tri C. [Stanford Univ., CA (United States); Lucile Packard Children's Hospital, Stanford, CA (United States)]·Wang, Austin T. [Stanford Univ., CA (United States)]·Wang, Sean K. [Stanford Univ., CA (United States)] (ORCID:0000000315578510)·Tan, Meng How [Nanyang Technological Univ. (Singapore)] (ORCID:0000000336275586)·Tan, Serena Y. [Stanford Univ., CA (United States)] (ORCID:0000000154090695)·Kosicki, Michael [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Genomics and System Biology Division] (ORCID:0000000171738852)·Pennacchio, Len A. [University of California, Berkeley, CA (United States); USDOE Joint Genome Institute (JGI), Berkeley, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Genomics and System Biology Division] (ORCID:0000000287483732)·Ben-David, Eyal [Illumina, Foster City, CA (United States)] (ORCID:0000000305140400)·Pasca, Anca M. [Stanford Univ., CA (United States)] (ORCID:0000000204459009)·Kundaje, Anshul [Stanford Univ., CA (United States)] (ORCID:0000000330842287)·Farh, Kyle K. H. [Illumina, Foster City, CA (United States)] (ORCID:0000000169478537)·Greenleaf, William J. [Stanford Univ., CA (United States)] (ORCID:0000000314093095)
View original source ↗Read source document ↗Export metadata ↓

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 expression1. Mapping accessible chromatin offers critical insights into transcriptional control, but available datasets for human development are restricted to bulk tissue, single organs or single modalities2. 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.

Explore related subjects

59 BASIC BIOLOGICAL SCIENCES

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Liu, Betty B. [Stanford Univ., CA (United States)] (ORCID:0000000316557164), Jessa, Selin [Stanford Univ., CA (United States)] (ORCID:0000000341926523), Kim, Samuel H. [Stanford Univ., CA (United States)] (ORCID:0000000183536190), Ng, Yan Ting [Illumina, Foster City, CA (United States); Nanyang Technological Univ. (Singapore)] (ORCID:0000000180758791), Higashino, Soon Il [Stanford Univ., CA (United States)], Marinov, Georgi K. [Stanford Univ., CA (United States)] (ORCID:0000000318227273), Chen, Derek C. [Stanford Univ., CA (United States)] (ORCID:0000000196524885), Parks, Benjamin E. [Stanford Univ., CA (United States)], Li, Li [Stanford Univ., CA (United States)] (ORCID:0000000178866056), Nguyen, Tri C. [Stanford Univ., CA (United States); Lucile Packard Children's Hospital, Stanford, CA (United States)], Wang, Austin T. [Stanford Univ., CA (United States)], Wang, Sean K. [Stanford Univ., CA (United States)] (ORCID:0000000315578510), Tan, Meng How [Nanyang Technological Univ. (Singapore)] (ORCID:0000000336275586), Tan, Serena Y. [Stanford Univ., CA (United States)] (ORCID:0000000154090695), Kosicki, Michael [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Genomics and System Biology Division] (ORCID:0000000171738852), Pennacchio, Len A. [University of California, Berkeley, CA (United States); USDOE Joint Genome Institute (JGI), Berkeley, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Environmental Genomics and System Biology Division] (ORCID:0000000287483732), Ben-David, Eyal [Illumina, Foster City, CA (United States)] (ORCID:0000000305140400), Pasca, Anca M. [Stanford Univ., CA (United States)] (ORCID:0000000204459009), Kundaje, Anshul [Stanford Univ., CA (United States)] (ORCID:0000000330842287), Farh, Kyle K. H. [Illumina, Foster City, CA (United States)] (ORCID:0000000169478537), Greenleaf, William J. [Stanford Univ., CA (United States)] (ORCID:0000000314093095). 2026-04-08. Multiomics and deep learning dissect regulatory syntax in human development. https://doi.org/10.1038/s41586-026-10326-9

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2026

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Genome-resolved insights into microbial diversity and elemental cycling in Winogradsky columns

We retained 18 MAGs with ≥50% completion and <10% contamination (i.e., at least medium quality). Of these, 10 had >90% completion and <5% contamination; however, only one (Paceibacteria Bin.003_MG) can be described as high-quality, as the others lacked a full suite of 5S, 16S, and 23S rRNA genes. To maximize the diversity of our recovered MAGs, we also retained one MAG (Chromatiaceae Bin.008_AM) with >40% (but less than 50%) completion and <5% contamination, as well as one (Rhodopseudomonas Bin.015_MK) with >90% completion and <20% (but>10%) contamination. Interestingly, significant chimerism was not detected in this MAG (40) , suggesting that the elevated contamination (20%) may instead reflect two closely related strains collapsing into a single bin. Consistent with this, contig coverage was bimodal, with roughly 17% of the assembly at ~115x and the remaining 83% at ~282x, while GC content remained uniform across both groups (~64%), arguing against contamination from a taxonomically distinct source.

59 BASIC BIOLOGICAL SCIENCES↗