Effective data visualization is vital for analyzing and communicating experimental results. However, most code-based plotting tools require substantial programming experience, posing a significant barrier to entry for life scientists. Tidyplots makes code-based plotting more accessible by offering an intuitive interface for generating highly customizable and informative plots.

Closely related transcription factor (TF) paralogs are facing the “specificity paradox”—they share similar binding motifs, but their cis-regulatory targets and physiological roles can be different. By applying high-throughput SELEX to 40 R2R3-MYB TFs, this study currently generates the largest data set illustrating the homodimeric specificities of plant TFs, while also reveals a yet unrecognized mechanism to solve the “specificity paradox”—a TF's binding specificity can change drastically upon homodimerization, and become unique across the whole family.

During the use of total parenteral nutrition (TPN), the decrease in the immune function of intestinal Group 3 innate lymphoid cells (ILC3s) can lead to an increased susceptibility to infections in patients. Specifically, the use of TPN causes dysbiosis of the gut microbiota, inhibiting the secretion of IL-22 by intestinal ILC3s, which in turn results in damage to the intestinal barrier. The reduction of Lactobacillus murinus (L. murinus) is an important factor in this process. Supplementing with L. murinus can increase the expression of its metabolite, indole-3-carboxylic acid (ICA). ICA promotes the secretion of IL-22 by ILC3s by targeting Rorγt, thereby improving the intestinal barrier and reducing susceptibility to infections. This study provides an important theoretical basis for using gut microbiota to regulate immune homeostasis in the treatment of clinical diseases.

Bacillus subtilis (B. subtilis) and its metabolite 2-hydroxy-4-methylpentanoic acid alleviated lipopolysaccharide (LPS)-induced intestinal epithelial barrier damage via the growth arrest and DNA damage 45A (GADD45A)-Wnt/β-catenin axis. LPS treatment led to a significant disruption of gut homeostasis. B. subtilis administration could restore gut homeostasis by alleviating inflammatory responses, increasing the abundance of beneficial bacteria, and enhancing the intestinal epithelial barrier.

A 4-month of time-restricted feeding (TRF) intervention alleviated cognitive impairments in Alzheimer's disease (AD) patients, while a 3-month TRF regimen improved spatial memory, reduced amyloid-beta accumulation, and promoted microglial aggregation around plaques in AD mice. Antibiotic-induced gut microbiota depletion partly abolished TRF's benefits. Through creatively integrating gut microbiota, metabolites, and hippocampal genes, Bifidobacterium pseudolongum (B. pseudolongum) and propionic acid (PA) were identified as key contributors to TRF's cognitive effects, with supplementation of either mimicking TRF's protective benefits. Positron emission tomography imaging revealed that PA directly crossed the blood-brain barrier, and PA supplementation restored disrupted metabolism in AD mice. Knockdown of its receptor free fatty acid receptor 3 (FFAR3) diminished TRF's protective effects. A case-control study showed a negative association between PA and cognitive status, while the TRF clinical intervention linked fecal PA to cognitive status. These findings suggest PA as a potential biomarker and underscore precise TRF-based nutritional interventions as a promising strategy for managing neurodegenerative diseases.

We developed an integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis (iMLGAM), an R package that combines various machine learning algorithms with genetic algorithms and multi-omics data to predict responses to immune checkpoint blockade (ICB) therapy. Utilizing pan-cancer tumor data, we established the iMLGAM scoring system to forecast ICB therapy outcomes. The system was validated through experimental methods and implemented as a Shiny web application. Clinical cohort validation further demonstrated its reliability in optimizing immunotherapy treatment decisions.

We developed an integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis (iMLGAM), an R package that combines various machine learning algorithms with genetic algorithms and multi-omics data to predict responses to immune checkpoint blockade (ICB) therapy. Utilizing pan-cancer tumor data, we established the iMLGAM scoring system to forecast ICB therapy outcomes. The system was validated through experimental methods and implemented as a Shiny web application. Clinical cohort validation further demonstrated its reliability in optimizing immunotherapy treatment decisions.

Preconception administration of antibiotics to female mice reduces the abundance of Limosilactobacillus reuteri in the maternal gut microbiota during pregnancy, subsequently affecting propionate levels. Decreased propionate levels downregulated the expression of Gdnf/Ret/Sox10 mediated by GPR41, leading to abnormal development of the enteric nervous system during the embryonic period. This dysplasia results in colonic dysmotility, impaired colonic epithelium, and increased susceptibility to water-avoidance stress in offspring.

This study dissects the genetic architecture of maize Root System Architecture, identifying significant root trait differences between tropical/subtropical and temperate lines. Using genome-wide association study, 3511 genes were linked to root morphology, weight, and slice traits. The candidate gene fucosyltransferase5 was validated for its role in root development and heat tolerance. Machine learning models based on root slice traits achieved high prediction accuracy, offering robust tools for ideotype-based molecular breeding and genetic enhancement of maize.

The specific knockout of intestinal hepatic leukemia factor (HLF) improved metabolic-associated fatty liver disease (MAFLD) by inhibiting peroxisome proliferator-activated receptor alpha (PPARα) and restoring the intestinal barrier. Study of the mechanism revealed that the HLF/PPARα axis regulated gut microbiota-derived extracellular vesicles (fEVs); which, through the gut-liver cycle, suppressed hepatocyte ferroptosis and reduced hepatic steatosis. Lipidomics and functional assays identified the conjugated bile acid taurochenodeoxycholic acid (TCDCA) as the key driver of the lipid-lowering effect of fEVs. The findings offer new therapeutic strategies for MAFLD.

This study presented two high-precision telomere-to-telomere genome assemblies for Min and Rongchang pigs, including a detailed exploration of the telomeric and centromeric regions. By integrating pan-genome and multi-omics analyses, structural variations linked to genetic adaptation were identified, providing a valuable resource for advancing pig breeding and genetic improvement.

This study assembled a high-quality chromosome-level genome of Prunus tomentosa, offering a vital resource for elucidating its genetic architecture, evolutionary relationships, and facilitating genome-assisted breeding efforts. Multi-omics integration revealed PtIMP3 and PtMIOX1L as key factors in cold tolerance of P. tomentosa. PtIMP3 drives the conversion of glucose-6-phosphate to myo-inositol, while PtMIOX1L catalyzes myo-inositol to d-glucuronic acid. Specifically, the high expression abundance of PtIMP3 and low expression abundance of PtMIOX1L resulted in high endogenous inositol levels in P. tomentosa. The application of myo-inositol enhanced the cold tolerance of cherry rootstocks by modulating reactive oxygen species concentrations and maintaining a stable relative water content. This finding supports the superior performance of P. tomentosa in adapting to extreme low-temperatures environmental conditions. These insights advance strategies for improving cold tolerance in horticultural crops, bridging fundamental research with practical applications in developing climate-resilient crops.

Chimeric RNAs from chromosomal rearrangements have long been validated as cancer markers and therapeutic targets for many years. Recently, trans-splicing and cis-splicing between adjacent genes are also shown to generate chimeric RNAs. They influence tumor progression by coding fusion proteins, acting as long noncoding or circular RNAs, or altering parental gene expression. Here, we analyzed chimeric RNAs from The Cancer Genome Atlas and Chinese Prostate Cancer Genome and Epigenome Atlas, identifying similarities and differences between Western and Chinese prostate cancer (PCa) cohorts. We confirmed distinct chimeric RNA expression patterns among cancer epithelial cells, cancer-associated fibroblasts, tumor-associated macrophages, and T cells. We unraveled how these chimeras impact tumor cell growth, stromal cell transformation, and intercellular communication within the microenvironment. This comprehensive study establishes a chimeric transcriptome atlas for Chinese PCa patients, highlights population-specific disparities, and presents validated chimeric RNAs with diagnostic, prognostic, and therapeutic potential.

The intricate bidirectional relationships among microbiota, microbial proteins, drugs, and diseases are essential for advancing precision medicine and minimizing adverse drug reactions. However, there are currently no data resources that comprehensively describe these valuable interactions. Therefore, the Microbiota-Drug Interaction and Disease Phenotype Interrelation Database (MDIPID) database was developed in this study. MDIPID is distinctive in its ability to elucidate the complex interactions among microbiota, microbial proteins, drugs/substances, and disease phenotypes, thereby providing a comprehensive interconnected network that facilitates the identification of microbial therapy targets and advances personalized medicine. This comprehensive resource is expected to become a popular repository for researchers aiming to identify microbial therapeutic targets, predict drug efficacy, and develop new therapies, thereby facilitating the advancement of personalized medicine. MDIPID can be accessed free without any login requirement at: https://idrblab.org/mdipid/.

In this study, we demonstrate that red light is the most critical light component for promoting healthy maize growth during Fusarium verticillioides infection. Red light receptors PHYTOCHROME B (PHYB) and C (PHYC) play essential roles in maize defense against this pathogen. Overexpression of PHYC in maize enhances resistance to F. verticillioides. Additionally, we identified two defense-related gene networks and some metabolites that reliant on PHYCs, involving key contributors such as WRKY transcription factors and metabolites like histamine and thiamine. Notably, the application of 50 μM histamine significantly boosts resistance, particularly under high-density conditions, marking the first report of the role of histamine in disease resistance in plants.

This study reports the first high-quality telomere-to-telomere (T2T) Rhododendron liliiflorum genome with 11 chromosomes that are gap free. The 24 telomeres and all 13 centromeres detected in this genome, which reached the highest quality gold level. In addition, other three Rhododendron species were sequenced and assembled to the chromosomal level. Based on 15 Rhododendron genomes, we conducted a pan-genome analysis of genus Rhododendron. Combining the genome and whole transcriptome sequencing, we identified several key genes and miRNAs related to the heat stress, which were further verified by transgenic experiments. Our findings provide rich resources for comparative and functional genomics studies of Rhododendron species.

The gut microbiota–cancer interaction functions through multi-level biological mechanisms, forming the basis for both diagnostic and therapeutic applications. Current technical and biological challenges drive the field toward precision medicine approaches, aiming to integrate multi-dimensional data for optimized, personalized cancer treatments.

Heavy metals are toxic and harmful pollutants that can affect the school environment and the exposed children's health. This study collected dust samples and children's fecal specimens, and performed gene sequencing. We used eXtreme Gradient Boosting to determine the impact of heavy metals on environmental microorganisms and gut microbiota, while using the relative length of the quadrant and Fourth-corner analysis to explore the relationship among the three components. We found heavy metal pollution existed in the classroom environment, with lead and copper significantly affecting environmental microorganisms' community structure. Although nonsignificant associations were observed between heavy metals and gut microbiota, Fourth-corner analysis revealed the associations were significantly mediated by environmental microorganisms. Both heavy metals and microorganisms in the environment can disrupt the microbial community structure in the intestines of exposed children.