Integration of multi-omics data can provide information on biomolecules from different layers to illustrate the complex biology systematically. Here, we build a multi-omics atlas containing 132,570 transcripts, 44,473 proteins, 19,970 phosphoproteins, and 12,427 acetylproteins across wheat vegetative and reproductive phases. Using this atlas, we elucidate transcriptional regulation network, contributions of post-translational modification (PTM) and transcript level to protein abundance, and biased homoeolog expression and PTM in wheat. The genes/proteins related to wheat development and disease resistance are systematically analyzed, thus identifying phosphorylation and/or acetylation modifications for the seed proteins controlling wheat grain quality and the disease resistance-related genes. Lastly, a unique protein module TaHDA9-TaP5CS1, specifying de-acetylation of TaP5CS1 by TaHDA9, is discovered, which regulates wheat resistance to Fusarium crown rot via increasing proline content. Our atlas holds great promise for fast-tracking molecular biology and breeding studies in wheat and related crops.
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http://dx.doi.org/10.1038/s41467-025-57550-x | DOI Listing |
Gastroenterology
March 2025
APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, Ireland.
Inflammatory bowel disease (IBD) is marked by significant clinical heterogeneity, posing challenges for accurate diagnosis and personalized treatment strategies. Conventional approaches, such as endoscopy and histology, often fail to adequately and accurately predict medium and long-term outcomes, leading to suboptimal patient management. Artificial intelligence (AI) is emerging as a transformative force enabling standardized, accurate, and timely disease assessment and outcome prediction, including therapeutic response.
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March 2025
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, Changchun 130012, Jilin Province, China.
Identifying genes causally linked to cancer from a multi-omics perspective is essential for understanding the mechanisms of cancer and improving therapeutic strategies. Traditional statistical and machine-learning methods that rely on generalized correlation approaches to identify cancer genes often produce redundant, biased predictions with limited interpretability, largely due to overlooking confounding factors, selection biases, and the nonlinear activation function in neural networks. In this study, we introduce a novel framework for identifying cancer genes across multiple omics domains, named ICGI (Integrative Causal Gene Identification), which leverages a large language model (LLM) prompted with causality contextual cues and prompts, in conjunction with data-driven causal feature selection.
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March 2025
Department of Hematology, Anqing Municipal Hospital, Anqing Hospital Affiliated to Anhui Medical University, Anqing, China.
Clinical management of acute myeloid leukemia (AML) poses significant challenges due to its poor prognosis and heterogeneous nature. Discovering new biomarkers is crucial for improving risk assessment and customizing treatment approaches. While leukocyte-specific transcript 1 (LST1) is implicated in inflammation and immune regulation, its function in AML remains ambiguous.
View Article and Find Full Text PDFBiophys Rep
February 2025
Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Advancements in molecular characterization technologies have accelerated targeted cancer therapy research at unprecedented resolution and dimensionality. Integrating comprehensive multi-omic molecular profiling of a tumor, proteogenomics, marks a transformative milestone for preclinical cancer research. In this paper, we initially provided an overview of proteogenomics in cancer research, spanning genomics, transcriptomics, and proteomics.
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
March 2025
Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
As a multidimensional metabolic disorder, the disability and death rate of type 2 diabetes mellitus (T2DM) has increased over time. T2DM covers a wide range of pathological manifestations ranging from hyperglycemia to multi-organ failure, and it has the potential to evolve into acute complications, including ketosis and chronic complications such as peripheral neuropathy, retinopathy, and nephropathy. T2DM mainly occurs in microvascular and large vessels and thus it is restricted for the clinician to diagnose and prescribe.
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