bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown
Опубликована: Ноя. 27, 2023
The sparse and stochastic nature of reprogramming has obscured our understanding how transcription factors drive cells to new identities. To overcome this limit, we developed a compact, portable system that increases direct conversion fibroblasts motor neurons by two orders magnitude. We show subpopulations with different potentials are distinguishable proliferation history. By controlling for history titrating each factor, find correlates levels the pioneer factor Ngn2, whereas shows biphasic response Lhx3. Increasing rate adult human generates morphologically mature, induced at high rates. Using optimized, polycistronic cassettes, generate graft murine central nervous system, demonstrating potential in vivo therapies.
Язык: Английский
Процитировано
4Predicting gene expression from histone marks using chromatin deep learning models depends on histone mark function, regulatory distance and cellular states
bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown
Опубликована: Март 29, 2024
Abstract To understand the complex relationship between histone mark activity and gene expression, recent advances have used in silico predictions based on large-scale machine learning models. However, these approaches omitted key contributing factors like cell state, function or distal effects, that impact relationship, limiting their findings. Moreover, downstream use of models for new biological insight is lacking. Here, we present most comprehensive study this to date - investigating seven marks, eleven types, across a diverse range states. We convolutional attention-based predict transcription from at promoters regulatory elements. Our work shows function, genomic distance cellular states collectively influence mark’s with transcription. found no individual consistently strongest predictor expression all contexts. This highlights need consider three when determining effect transcriptional state. Furthermore, conducted perturbation assays, uncovering functional disease related loci highlighting frameworks chromatin deep uncover insight. Graphical abstract
Язык: Английский
Процитировано
1Interpreting the CTCF-mediated sequence grammar of genome folding with AkitaV2
bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown
Опубликована: Авг. 4, 2024
Abstract Interphase mammalian genomes are folded in 3D with complex locus-specific patterns that impact gene regulation. CTCF (CCCTC-binding factor) is a key architectural protein binds specific DNA sites, halts cohesin-mediated loop extrusion, and enables long-range chromatin interactions. There hundreds of thousands annotated CTCF-binding sites genomes; disruptions some result distinct phenotypes, while others have no visible effect. Despite their importance, the determinants which necessary for genome folding regulation remain unclear. Here, we update utilize Akita, convolutional neural network model, to extract sequence preferences grammar contributing folding. Our analyses individual reveal four predictions: (i) only small fraction genomic impactful, (ii) insulation strength highly dependent on sequences flanking core binding motif, (iii) broadly compatible, (iv) nucleotides contribute largely additively overall strength. analysis collections make two predictions multi-motif grammar: depends number within cluster, pattern formation governed by orientation spacing these rather than any inherent specialization motifs themselves. In sum, present framework using models probe instructing provide guide future experimental inquiries. Author Summary Mammalian spatially organized profound consequences all processes involving DNA. organizer, recognizing numerous creating variety contact across genome. importance CTCF, how collectively instruct This work leverages ability deep network, high-throughput after perturbations. Using several experimentally testable predictions. First, minority individually folding, greatly modulate impact. Second, multiple together influence based number, orientation, spacing. roadmap interpreting networks better understand important considerations design experiments.
Язык: Английский
Процитировано
1Predicting gene expression from histone marks using chromatin deep learning models depends on histone mark function, regulatory distance and cellular states
Nucleic Acids Research, Год журнала: 2024, Номер unknown
Опубликована: Дек. 9, 2024
To understand the complex relationship between histone mark activity and gene expression, recent advances have used in silico predictions based on large-scale machine learning models. However, these approaches omitted key contributing factors like cell state, function or distal effects, which impact relationship, limiting their findings. Moreover, downstream use of models for new biological insight is lacking. Here, we present most comprehensive study this to date - investigating seven marks eleven types across a diverse range states. We convolutional attention-based predict transcription from at promoters regulatory elements. Our work shows that function, genomic distance cellular states collectively influence mark's with transcription. found no individual consistently strongest predictor expression all contexts. This highlights need consider three when determining effect transcriptional state. Furthermore, conducted perturbation assays, uncovering functional disease related loci highlighting frameworks chromatin deep uncover insight.
Язык: Английский
Процитировано
0Progress in multifactorial single-cell chromatin profiling methods
Biochemical Society Transactions, Год журнала: 2024, Номер 52(4), С. 1827 - 1839
Опубликована: Июль 18, 2024
Chromatin states play a key role in shaping overall cellular and fates. Building complete picture of the functional state chromatin cells requires co-detection several distinct biochemical aspects. These span DNA methylation, accessibility, chromosomal conformation, histone posttranslational modifications, more. While this certainly presents challenging task, over past few years many new creative methods have been developed that now enable co-assay these different aspects at single cell resolution. This field is entering an exciting phase, where confluence technological improvements, decreased sequencing costs, computational innovation are presenting opportunities to dissect diversity present tissues, how may influence gene regulation. In review, I discuss spectrum current experimental approaches for multifactorial profiling, highlight some analytical challenges, as well areas further innovation.
Язык: Английский
Процитировано
0Systems immunology approaches to study T cells in health and disease
npj Systems Biology and Applications, Год журнала: 2024, Номер 10(1)
Опубликована: Окт. 9, 2024
T cells are dynamically regulated immune that implicated in a variety of diseases ranging from infection, cancer and autoimmunity. Recent advancements sequencing methods have provided valuable insights the transcriptional epigenetic regulation various disease settings. In this review, we identify key sequencing-based been applied to understand transcriptomic epigenomic diseases.
Язык: Английский
Процитировано
0Jade1 and the HBO1 complex are spatial-selective cofactors of Oct4
bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown
Опубликована: Ноя. 7, 2024
Abstract Oct4 is a master regulator of pluripotency. Potential interactors have been cataloged extensively but the manner and significance these interactions are incompletely defined. Like other POU domain proteins, capable binding to DNA in multiple configurations, however relationship between configurations cofactor recruitment (and hence transcription output) unknown. Here, we show that interacts with common unique proteins when bound different configurations. One Jade1, component HBO histone acetyltransferase complex. Jade1 preferentially associates M ore palindromic O ctamer- R elated E lement (MORE) sequences bind dimers associated strong gene expression. Surprisingly, find N-terminal activation domain, rather than facilitating binding, serves as an autoinhibitory dampens interaction. ChIP-seq using HBO1, enzymatic complex, identifies preference for adjacent at MORE sites. Using purified recombinant nucleosome complexes, HBO1 complex acetylates H3K9 within nucleosomes more efficiently co-bound site. Cryo-electron microscopy reveals near entry/exit site partially unwinds from core particles, additional mass These results identify novel mechanism transcriptional regulation by Oct4.
Язык: Английский
Процитировано
0RegVelo: gene-regulatory-informed dynamics of single cells
bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown
Опубликована: Дек. 11, 2024
Abstract RNA velocity has emerged as a popular approach for modeling cellular change along the phenotypic landscape but routinely omits regulatory interactions between genes. Conversely, methods that infer gene networks (GRNs) do not consider dynamically changing nature of biological systems. To integrate these two currently disconnected fields, we present RegVelo, an end-to-end dynamic, interpretable, and actionable deep learning model learns joint splicing kinetics relationships allows us to perform in silico perturbation predictions. When applied datasets cell cycle, human hematopoiesis, murine pancreatic endocrinogenesis, RegVelo demonstrates superior predictive power simulations, example, compared focus solely on dynamics or GRN inference. leverage RegVelo’s full potential, studied zebrafish neural crest development underlying mechanisms using our Smart-seq3 dataset shared expression chromatin accessibility measurements. Using predictions, validated by CRISPR/Cas9-mediated knockout single-cell Perturb-seq, establish transcription factor tfec early driver elf1 novel regulator pigment fate propose gene-regulatory circuit involving via toggle-switch model.
Язык: Английский
Процитировано
0Epigenome Analysis
Elsevier eBooks, Год журнала: 2024, Номер unknown
Опубликована: Янв. 1, 2024
Процитировано
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