The investigation of correlations between radiomic and genomic profiling in breast cancer (BC) molecular subtypes is crucial for understanding disease mechanisms and providing personalized treatment. We present a well-designed radiogenomic framework—image-gene-gene set (IMAGGS), which detects multi-way associations in BC subtypes by integrating radiomic and genomic features.Our dataset consists of 721 patients, each of whom has 12 ultrasound (US) images captured from different angles and gene mutation data. To better characterize tumor traits, 12 multi-angle US images are fused using two distinct strategies. Then, we analyze complex many-to-many associations between phenotypic and genotypic features using a machine learning algorithm, deviating from the prevalent one-to-one relationship pattern observed in previous studies. Key radiomic and genomic features are screened using these associations. In addition, gene set enrichment analysis is performed to investigate the joint effects of gene sets and delve deeper into the biological functions of BC subtypes. We further validate the feasibility of IMAGGS in a glioblastoma multiforme dataset to demonstrate the scalability of IMAGGS across different modalities and diseases. Taken together, IMAGGS provides a comprehensive characterization for diseases by associating imaging, genes, and gene sets, paving the way for biological interpretation of radiomics and development of targeted therapy.

Polycystic ovary syndrome (PCOS) is a highly familial and heritable endocrine disorder. Over half of the daughters born to women with PCOS may eventually develop their own PCOS-related symptoms. Progress in the treatment of PCOS is currently hindered by the complexity of its clinical manifestations and incomplete knowledge of its etiopathogenesis. Various animal models, including experimentally-induced, naturally-occurring, and spontaneously-arising ones, have been established to emulate a wide range of phenotypical and pathological traits of human PCOS. These studies have led to a paradigm shift for understanding the genetic,developmental, and evolutionary origins of this disorder. Furthermore, emerging evidence suggests that animal models are useful in evaluating state-of-the-art drugs and treatments for PCOS. This review aims to provide a comprehensive summary of recent studies of PCOS in animal models, highlighting the power of these disease models in understanding the biology of PCOS and aiding high-throughput approaches.

T-box transcription factor T (TBXT; T) is required for mesodermal formation and axial skeletal development. Although it has been extensively studied in various model organisms, human congenital vertebral malformations (CVMs) involving T are not well established. Here, we report a family with 15 CVM patients distributed across four generations. All affected individuals carry a heterozygous mutation, T c.596A>G (p.Q199R), which is not found in unaffected family members, indicating co-segregation of the genotype and phenotype. In vitro assays show that T p.Q199R increases the nucleocytoplasmic ratio and enhances its DNA-binding affinity, but reduces its transcriptional activity compared to the wild-type. To determine the pathogenicity of this mutation in vivo, we generated a Q199R knock-in mouse model that recapitulates the human CVM phenotype. The heterozygous Q199R mice show subtle kinked or shortened tails, while the homozygous mice exhibit tail filaments and severe vertebral deformities. Overall, we show that the Q199R mutation in T causes CVM in humans and mice, providing new evidence supporting the function of T in the genetic etiology of human CVM.

Wheat (Triticum aestivum) is one of the most essential human energy and protein sources. However, wheat production is threatened by devastating fungal diseases, such as stripe rust, caused by Puccinia striiformis Westend. f. sp. tritici(Pst). Here, we reveal that the alternations in chloroplast lipid profiles and the accumulation of jasmonate (JA) in the necrosis region activate JA signaling and trigger the host defense. The collapse of chloroplasts in the necrosis region results in accumulations of polyunsaturated membrane lipids and the lipid-derived phytohormone, JA, in transgenic lines of Yr36 that encodes Wheat Kinase START 1 (WKS1), a high-temperature-dependent adultplant resistance protein. WKS1.1, a protein encoded by a full-length splicing variant of WKS1, phosphorylates and enhances the activity of keto-acyl thiolase (KAT-2B), a critical enzyme catalyzing the β-oxidation reaction in JA biosynthesis. The premature stop mutant, kat-2b, accumulates less JA and shows defects in the host defense against Pst. Conversely, over-expression of KAT-2B results in a higher level of JA and limits the growth of Pst. Moreover, JA inhibits the growth and reduces pustule densities of Pst. This study illustrates the WKS1.1-KAT-2B-JA pathway enhancing wheat defense against fungal pathogens to attenuate yield loss.

Creating a multi-gene alignment matrix for phylogenetic analysis using organelle genomes involves aligning single-gene datasets manually, a process that can be time-consuming and prone to errors. The HomBlocks pipeline has been created to eliminate the inaccuracies arising from manual operations. The processing of a large number of sequences, however, remains a time- consuming task. To conquer this challenge, we develop a speedy and efficient method called Organelle Genomes for Phylogenetic Analysis (ORPA). ORPA can quickly generate multiple sequence alignments for whole-genome comparisons by parsing the result files of NCBI BLAST, completing the task in just one minute. With increasing data volume, the efficiency of ORPA is even more pronounced, over 300 times faster than HomBlocks in aligning 60 high-plant chloroplast genomes. The phylogenetic tree outputs from ORPA are equivalent to HomBlocks, indicating its outstanding efficiency. Due to its speed and accuracy, ORPA can identify species- level evolutionary conflicts, providing valuable insights into evolutionary cognition.

Coordinated plant adaptation involves the interplay of multiple traits driven by habitat- specific selection pressures. Pleiotropic effects, wherein genetic variants of a single gene control multiple traits, can expedite such adaptations. Until present, only a limited number of genes have been reported to exhibit pleiotropy. Here, we create a recombinant inbred line (RIL) population derived from two Arabidopsis thaliana (A. thaliana) ecotypes originating from divergent habitats. Using this RIL population, we identify an allelic variation in a MADS-box transcription factor, SHORT VEGETATIVE PHASE (SVP), which exerts a pleiotropic effect on leaf size and drought-versus-humidity tolerance. Further investigation reveals that a natural null variant of the SVP protein disrupts its normal regulatory interactions with target genes, including GRF3, CYP707A1/3, and AtBG1, leading to increased leaf size, enhanced tolerance to humid conditions, and changed in flowering time in humid conditions in A. thaliana. Remarkably, polymorphic variations in this gene have been traced back to early A. thaliana populations, providing a genetic foundation and plasticity for subsequent colonization of diverse habitats by influencing multiple traits. These findings advance our understanding of how plants rapidly adapt to changing environments by virtue of the pleiotropic effects of individual genes on multiple trait alterations.

Monogenic disorders refer to a group of human diseases caused by mutations in single genes. While disease-modifying therapies have offered some relief to symptoms and delayed progression for some monogenic diseases, most of these diseases still lack effective treatments. In recent decades, gene therapy has emerged as a promising therapeutic strategy for genetic disorders. Researchers have developed various gene manipulation tools and gene delivery systems to treat monogenic diseases. Despite this progress, concerns about inefficient delivery, persistent expression, immunogenicity, toxicity, capacity limitation, genomic integration, and limited tissue specificity still need to be addressed. This review gives an overview of commonly used gene therapy and delivery tools, along with the challenges they face and the potential strategies to counter them.

Messenger RNA (mRNA) translation consists of initiation, elongation, termination, and ribosome recycling, carried out by the translation machinery, primarily including tRNAs, ribosomes, and translation factors (TrFs). Translational regulators transduce signals of growth and development, as well as biotic and abiotic stresses, to the translation machinery, where global or selective translational control occurs to modulate mRNA translation efficiency (TrE). As the basis of translational control, the translation machinery directly determines the quality and quantity of newly synthesized peptides and, ultimately, the cellular adaption. Thus, regulating the availability of diverse machinery components is reviewed as the central strategy of translational control. We provide classical signaling pathways (e.g., integrated stress responses) and cellular behaviors (e.g., liquid-liquid phase separation) to exemplify this strategy within different physiological contexts, particularly during host-microbe interactions. With new technologies developed, further understanding this strategy will speed up translational medicine and translational agriculture.

Osteoarthritis (OA) is one of the most common degenerative joint diseases worldwide, causing pain, disability, and decreased quality of life. The balance between regeneration and inflammation-induced degradation results in multiple etiologies and complex pathogenesis of OA. Currently, there is a lack of effective therapeutic strategies for OA treatment. With the development of CRISPR-based genome, epigenome, and RNA editing tools, OA treatment has been improved by targeting genetic risk factors, activating chondrogenic elements, and modulating inflammatory regulators. Supported by cell therapy and in vivo delivery vectors, genome, epigenome, and RNA editing tools may provide a promising approach for personalized OA therapy. This review summarizes CRISPR-based genome, epigenome, and RNA editing tools that can be applied to the treatment of OA and provides new insights into the development of CRISPR-based therapeutics for OA treatment. Moreover, in-depth evaluations of the efficacy and safety of these tools in human OA treatment are needed.

The immune regulatory effects of probiotics have been widely recognized to be strain-specific. However it is unknown if there is a species- or genus-dependent manner. In this study, we use an in vitro mesenteric lymph node (MLN) model to systematically evaluate the immunostimulatory effects of gut-derived potential probiotics. The results exhibite an obvious species or genus consensus immune response pattern. RNA-seq shows that T cell-dependent B cell activation and antibody responses may be inherent to this model. Of the five tested genera, Akkermansia spp. and Clostridium butyrium directly activate the immune response in vitro, as indicated by the secretion of interleukin-10. Bifidobacterium spp. and Bacteroides spp. activate immune response with the help of stimuli (anti-CD3 and anti-CD28 antibodies). Lactobacillus spp. blunt the immune response with or without stimuli. Further investigations show that the cell surface protein of A. muciniphila AH39, which may serve as a T cell receptor cognate antigen, might evoke an in vitro immune activation. In vivo, oral administration of A. muciniphila AH39 influences the proportion of T regulatory cells (Tregs) in MLNs and the spleen under homeostasis in both specific pathogen-free and germ-free mice. All these findings indicate the distinct effects of different genera or species of potential gut-derived probiotics on intestinal and systemic immunity.