bims-gerecp 2025-01-12 papers

Issue of 2025–01–12
seven papers selected by
Xiao Qin, University of Oxford

Nature. 2025 Jan 08.

Crypt density and recruited enhancers underlie intestinal tumour initiation.

Liam Gaynor, Harshabad Singh, Guodong Tie, Krithika Badarinath, Shariq Madha, Andrew Mancini, Swarnabh Bhattacharya, Mikio Hoshino, Frederic J de Sauvage, Kazutaka Murata, Unmesh Jadhav, Ramesh A Shivdasani.

Oncogenic mutations that drive colorectal cancer can be present in healthy intestines for long periods without overt consequence1,2. Mutation of Adenomatous polyposis coli (Apc), the most common initiating event in conventional adenomas3, activates Wnt signalling, hence conferring fitness on mutant intestinal stem cells (ISCs)4,5. Apc mutations may occur in ISCs that arose by routine self-renewal or by dedifferentiation of their progeny. Although ISCs of these different origins are fundamentally similar6,7, it is unclear if both generate tumours equally well in uninjured intestines. Also unknown is whether cis-regulatory elements are substantively modulated upon Wnt hyperactivation or as a feature of subsequent tumours. Here, we show in two mouse models that adenomas are not an obligatory outcome of Apc deletion in either ISC source but require proximity of mutant intestinal crypts. Reduced crypt density abrogates, and aggregation of mutant colonic crypts augments, adenoma formation. Moreover, adenoma-resident ISCs open chromatin at thousands of enhancers that are inaccessible in Apc-null ISCs not associated with adenomas. These cis-elements explain adenoma-selective gene activity and persist, with little further expansion of the repertoire, as other oncogenic mutations accumulate. Thus, cooperativity between neighbouring mutant crypts and new accessibility at specific enhancers are key steps early in intestinal tumourigenesis.

DOI: https://doi.org/10.1038/s41586-024-08573-9

Nature. 2025 Jan 08.

A foundation model of transcription across human cell types.

Xi Fu, Shentong Mo, Alejandro Buendia, Anouchka P Laurent, Anqi Shao, Maria Del Mar Alvarez-Torres, Tianji Yu, Jimin Tan, Jiayu Su, Romella Sagatelian, Adolfo A Ferrando, Alberto Ciccia, Yanyan Lan, David M Owens, Teresa Palomero, Eric P Xing, Raul Rabadan.

Transcriptional regulation, which involves a complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate to unseen cell types and conditions. Here we introduce GET (general expression transformer), an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types1,2. Relying exclusively on chromatin accessibility data and sequence information, GET achieves experimental-level accuracy in predicting gene expression even in previously unseen cell types3. GET also shows remarkable adaptability across new sequencing platforms and assays, enabling regulatory inference across a broad range of cell types and conditions, and uncovers universal and cell-type-specific transcription factor interaction networks. We evaluated its performance in prediction of regulatory activity, inference of regulatory elements and regulators, and identification of physical interactions between transcription factors and found that it outperforms current models4 in predicting lentivirus-based massively parallel reporter assay readout5,6. In fetal erythroblasts7, we identified distal (greater than 1 Mbp) regulatory regions that were missed by previous models, and, in B cells, we identified a lymphocyte-specific transcription factor-transcription factor interaction that explains the functional significance of a leukaemia risk predisposing germline mutation8-10. In sum, we provide a generalizable and accurate model for transcription together with catalogues of gene regulation and transcription factor interactions, all with cell type specificity.

DOI: https://doi.org/10.1038/s41586-024-08391-z

Nature. 2025 Jan 08.

AI learns from chromatin data to uncover gene interactions.

Alicja Brożek, Christina V Theodoris.

Keywords: Computational biology and bioinformatics; Epigenetics; Genetics; Machine learning

DOI: https://doi.org/10.1038/d41586-024-04107-5

Nat Cell Biol. 2025 Jan 09.

Transcription factor networks in cellular quiescence.

Mithun Mitra, Sandra L Batista, Hilary A Coller.

Many of the cells in mammalian tissues are in a reversible quiescent state; they are not dividing, but retain the ability to proliferate in response to extracellular signals. Quiescence relies on the activities of transcription factors (TFs) that orchestrate the repression of genes that promote proliferation and establish a quiescence-specific gene expression program. Here we discuss how the coordinated activities of TFs in different quiescent stem cells and differentiated cells maintain reversible cell cycle arrest and establish cell-protective signalling pathways. We further cover the emerging mechanisms governing the dysregulation of quiescence TF networks with age. We explore how recent developments in single-cell technologies have enhanced our understanding of quiescence heterogeneity and gene regulatory networks. We further discuss how TFs and their activities are themselves regulated at the RNA, protein and chromatin levels. Finally, we summarize the challenges associated with defining TF networks in quiescent cells.

DOI: https://doi.org/10.1038/s41556-024-01582-w

Nat Genet. 2025 Jan 08.

Profiling the epigenome using long-read sequencing.

Tianyuan Liu, Ana Conesa.

The advent of single-molecule, long-read sequencing (LRS) technologies by Oxford Nanopore Technologies and Pacific Biosciences has revolutionized genomics, transcriptomics and, more recently, epigenomics research. These technologies offer distinct advantages, including the direct detection of methylated DNA and simultaneous assessment of DNA sequences spanning multiple kilobases along with their modifications at the single-molecule level. This has enabled the development of new assays for analyzing chromatin states and made it possible to integrate data for DNA methylation, chromatin accessibility, transcription factor binding and histone modifications, thereby facilitating comprehensive epigenomic profiling. Owing to recent advancements, alternative, nascent and translating transcripts can be detected using LRS approaches. This Review discusses LRS-based experimental and computational strategies for characterizing chromatin states and highlights their advantages over short-read sequencing methods. Furthermore, we demonstrate how various long-read methods can be integrated to design multi-omics studies to investigate the relationship between chromatin states and transcriptional dynamics.

DOI: https://doi.org/10.1038/s41588-024-02038-5

Life (Basel). 2024 Dec 07. pii: 1622. [Epub ahead of print]14(12):

The "Culture" of Organs: A Holistic Theory on the Origins of the Cancer Tissue Environment.

Robert D Rehnke.

For over a century, the somatic gene mutation theory of cancer has been a scientific orthodoxy. The recent failures of causal explanations using this theory and the lack of significant progress in addressing the cancer problem medically have led to a new competition of ideas about just what cancer is. This essay presents an alternative view of cancer as a developmental process gone wrong. More specifically, cancer is a breakdown in the autopoietic process of organ maintenance and the multicellular coordination of tissues. Breast cancer is viewed through a systems science perspective as an example of the importance of framing one's theoretical assumptions before making empirical judgments. Finally, a new understanding of the histoarchitecture of the interstitium is presented as a first principle of cancer: a process of cells coming from cells, invading the space between cells.

Keywords: breast cancer; cancer; cancer tissue environment; developmental autopoiesis; epithelial parenchyma; interstitium; intra-organic spaces; mesenchyme; ontogenesis; reticular fascial network

DOI: https://doi.org/10.3390/life14121622