PubMed · 16738558
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Harmen J Bussemaker. 2006-04-18. Modeling gene expression control using Omes Law.. https://doi.org/10.1038/msb4100055
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MOTIVATION: Identifying regulatory elements in various chromosomal regions that influence gene expression is a fundamental challenge in epigenomics, with profound implications for understanding gene regulation and disease mechanisms. The advent of paired single-cell RNA sequencing and single-cell ATAC sequencing has created unprecedented opportunities to address this challenge by enabling simultaneous profiling of gene expression and chromatin accessibility at single-cell resolution. However, the inherent signals between them are weak due to the highly sparse and noisy nature of data. RESULTS: This article proposes single-cell meta-Path based Omics Embedding (scPOEM), a novel embedding method that jointly projects chromatin accessibility peaks and expressed genes into a shared low-dimensional space. By integrating the relationships among peak-peak, peak-gene, and gene-gene interactions, scPOEM assigns closer representations in the embedding space to related peak-gene pairs. Our experiments demonstrate that scPOEM generates stable representations of peaks and genes, outperforms existing methods in recovering biologically meaningful peak-gene regulatory relationships and enables new insights in subgroup and differential analysis of gene regulation. These results highlight its potential to uncover gene regulatory mechanisms and enhance the understanding of transcriptional regulation at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: The source code of scPOEM is available at https://github.com/Houyt23/scPOEM. The datasets can be obtained from the 10× Genomics (https://www.10xgenomics.com/datasets/pbmc-from-a-healthy-donor-granulocytes-removed-through-cell-sorting-10-k-1-standard-1-0-0) and GEO database under access codes GSE194122 and GSE239916.
Temperature has a strong influence on most individual biochemical reactions. Despite this, many organisms have the remarkable ability to keep certain physiological fluxes approximately constant over an extended temperature range. In this study, we show how temperature compensation can be considered as a pathway phenomenon rather than the result of a single-enzyme property. Using metabolic control analysis, it is possible to identify reaction networks that exhibit temperature compensation. Because most activation enthalpies are positive, temperature compensation of a flux can occur when certain control coefficients are negative. This can be achieved in networks with branching reactions or if the first irreversible reaction is regulated by a feedback loop. Hierarchical control analysis shows that networks that are dynamic through regulated gene expression or signal transduction may offer additional possibilities to bring the apparent activation enthalpies close to zero and lead to temperature compensation. A calorimetric experiment with yeast provides evidence that such a dynamic temperature adaptation can actually occur.
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