Non-coding cis-regulatory variants in animal genomes are an important driving force in the evolution of transcription regulation and phenotype diversity. However, cistrome dynamics in plants remain largely underexplored. Here, we compare the binding of GOLDEN2-LIKE (GLK) transcription factors in tomato, tobacco, Arabidopsis, maize and rice. Although the function of GLKs is conserved, most of their binding sites are species-specific. Conserved binding sites are often found near photosynthetic genes dependent on GLK for expression, but sites near non-differentially expressed genes in the glk mutant are nevertheless under purifying selection. The binding sites' regulatory potential can be predicted by machine learning model using quantitative genome features and TF co-binding information. Our study show that genome cis-variation caused wide-spread TF binding divergence, and most of the TF binding sites are genetically redundant. This poses a major challenge for interpreting the effect of individual sites and highlights the importance of quantitatively measuring TF occupancy.
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http://dx.doi.org/10.1038/s41467-022-35438-4 | DOI Listing |
Mikrochim Acta
January 2025
Key Laboratory of New Energy & New Functional Materials, Shaanxi Key Laboratory of Chemical Reaction Engineering, College of Chemistry and Chemical Engineering, School of Medicine, Yan'an University, Yan'an, Shaanxi, 716000, People's Republic of China.
Dexamethasone sodium phosphate (DSP) and betamethasone sodium phosphate (BSP) imprinted hydrogels embedded with two-dimensional photonic crystals (2DPC) were developed as hormones-sensitive photonic hydrogel sensors with highly sensitive, selective, anti-interference and reproducible recognition capability. The DSP/BSP molecularly imprinted photonic hydrogels (denoted as DSP-MIPH and BSP-MIPH) can specifically recognize DSP/BSP by rebinding the DSP/BET molecules to nanocavities in the hydrogel network. This recognition is enabled by the similar shape, size, and binding sites of the nanocavities to the target molecules.
View Article and Find Full Text PDFMater Horiz
January 2025
School of Chemistry, UNSW Sydney, Sydney, NSW 2052, Australia.
Patterning soft materials with cell adhesion motifs can be used to emulate the structures found in natural tissues. While patterning in tissue is driven by cellular assembly, patterning soft materials in the laboratory most often involves light-mediated chemical reactions to spatially control the presentation of cell binding sites. Here we present hydrogels that are formed with two responsive crosslinkers-an anthracene-maleimide adduct and a disulfide linkage-thereby allowing simultaneous or sequential patterning using force and UV light.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Donghua University, No.2999, North Renmin Road, Songjiang District, Shanghai, CHINA.
Herein, we demonstrate a two-in-one strategy for efficient neutral electrosynthesis of H2O2 via two-electron oxygen reduction reaction (2e-ORR), achieved by synergistically fine-modulating both the local microenvironment and electronic structure of indium (In) single atom (SA) sites. Through a series of finite elemental simulations and experimental analysis, we highlight the significant impact of phosphorous (P) doping on an optimized 2D mesoporous carbon carrier, which fosters a favorable microenvironment by improving the mass transfer and O2 enrichment, subsequently leading to an increased local pH levels. Consequently, an outstanding 2e-ORR performance is observed in neutral electrolytes, achieving over 95% selectivity for H2O2 across a broad voltage range of 0.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
Laboratory for Molecular Infection Medicine Sweden (MIMS), Umeå University, Biomedicinbyggnaden 6K och 6L, Umeå universitetssjukhus, 901 87, Umeå, Sweden.
Single-cell RNA-seq methods can be used to delineate cell types and states at unprecedented resolution but do little to explain why certain genes are expressed. Single-cell ATAC-seq and multiome (ATAC + RNA) have emerged to give a complementary view of the cell state. It is however unclear what additional information can be extracted from ATAC-seq data besides transcription factor binding sites.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
School of Information Science & Engineering, Lanzhou University, Lanzhou 730000, China.
Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug development process. Recently, deep learning models have been widely applied to DTA prediction and have achieved notable success. However, existing methods often encounter several common issues: first, the data representations lack sufficient information; second, the extracted features are not comprehensive; and third, most methods lack interpretability when modeling drug-target binding.
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