Super enhancers (SEs) are crucial regulatory elements in the genome that determine cell identity and fate commitment through mechanisms such as recruiting transcription factors (TFs), interacting with super enhancers RNAs (seRNAs), and phase separation. This ensures accurate gene expression in response to both environmental and intrinsic signals. Advances in 3D genome architecture have further illuminated how SEs are organized and regulated within the nucleus, thereby enhancing our understanding of their function. Recent innovations in genomic technologies, including chromatin accessibility, CRISPR-Cas9, 3C-based methods and imaging methods, have revolutionized the study of SEs. These technologies have facilitated precise mapping and functional characterization, providing deeper insights into how SEs influence gene regulation. In particular, these advancements offer promising potential for exploring SE dynamics in livestock improvement, opening avenues for the enhancement of agricultural and breeding practices.

Gene detection chip design critically depends on oligonucleotide probe hybridization efficiency, yet conventional thermodynamic models for its evaluation diverge from experiments, and the lack of comprehensive universal datasets further stops models from reflecting real probe behaviors. To address these issues, a dataset with 8 subsets (over 3.8million probes) was first constructed by integrating public microarray data. We then propose TransHybrid-a sequence-based deep learning framework that embeds complementary strand features into a Transformer architecture. The validation and test results show that the performance of TransHybrid, as measured by the Pearson correlation coefficient (PCC), is more than double that of traditional thermodynamic models, significantly outperforming conventional evaluation methods. The robustness of our model was validated via our independent experimental dataset, which was constructed through a series of designed experiments for fine-tuning TransHybrid. Following fine-tuning on this custom dataset, TransHybrid achieved a 25% improvement over the PCC of the thermodynamic models. Furthermore, mechanistic analyses revealed that TransHybrid captures biologically meaningful sequence features, such as the contribution of GC-rich regions, and provides interpretable attention maps. These findings demonstrate the superior ability of TransHybrid to accurately model hybridization efficiency, paving the way for more effective probe design in gene detection applications.

Skeletal muscle fiber composition plays a critical role in determining muscle growth and meat quality in livestock species. However, the molecular mechanisms underlying muscle fiber-type transformation in meat rabbits remain poorly understood. Here, we integrated transcriptomic and label-free proteomic analyses to investigate skeletal muscle development in Ira rabbits at three developmental stages (D0, D35, and D70). Immunofluorescence staining revealed a gradual increase in slow-twitch muscle fibers in the gastrocnemius during postnatal growth. Enzyme activity assays showed decreased lactate dehydrogenase (LDH) activity and increased succinate dehydrogenase (SDH) activity, indicating a metabolic shift toward oxidative metabolism. Transcriptomic analysis identified thousands of differentially expressed genes across developmental stages, whereas proteomic profiling revealed numerous differentially expressed proteins associated with metabolic pathways. We identified ten candidate genes (NOS1, CASQ2, ANKRD1, ANKRD2, CXCL10, GPC3, NEDD4, MYORG, MYLK2, EZH2) and nine key proteins (TRAF3IP3, APBB2, PGK1, TMCO5A, PKM, PVALB, PDLIM7, PHKG1, PHKA1) that may be associated with muscle fiber-type transformation during postnatal skeletal muscle development. Functional enrichment analysis indicated that these molecules were associated with multiple metabolic pathways including glycolysis/gluconeogenesis and butanoate metabolism. These findings provide a multi-omics perspective on skeletal muscle development in rabbits and contribute to a better understanding of the molecular basis of muscle fiber-type transformation during postnatal growth.

Yanyun (YY) sheep are a composite breed developed by targeted crossbreeding of Dorper, Hu, and East Friesian sheep to improve growth, reproduction, and environmental adaptability, yet the genomic basis underlying their formation and selective improvement remains unclear. Whole-genome analyses showed that YY sheep retain moderate genetic diversity with low genomic inbreeding (FROH), indicating limited autozygosity. Population structure analyses supported that YY sheep form a genetically distinct yet admixed group consistent with their breeding history. Genome-wide selection scans identified multiple candidate regions associated with growth, metabolism, reproduction, immune function, and environmental adaptability, including loci showing consistent differentiation and haplotype-based selection signals across multiple population comparisons. These results provide a genome-wide view of the genetic diversity, population structure, and selection landscape of YY sheep, and identify candidate genomic regions for future investigation of economically important and adaptive traits in composite sheep breeding.

Understanding recombination rates is crucial in evolutionary biology, as recombination shapes genetic diversity, natural selection, and adaptation. We investigated recombination rate variation in Chironomus riparius across different latitudes, seasons, and experimental treatments using Pool-seq data from five studies and the ReLERNN neural network-based method. We examined its relationship with genetic diversity, GC content, and FST, assessing causality through structural equation modeling. In natural populations, recombination rates showed no clear latitudinal pattern, likely due to interactions between climate-driven selection, demographic history and regional environmental heterogeneity. However, seasonal variation was evident, with higher recombination rates in autumn than winter, possibly due to temperature-induced plasticity or seasonal bottlenecks. A cold snap in March 2018 triggered a sharp recombination increase, potentially suggesting a stress-induced adaptive response. Across datasets, recombination rates were correlated with genetic diversity and other genomic parameters, with structural equation models (SEMs) indicating that recombination and selection jointly shape patterns of π and differentiation, while relationships with GC content and TEs counts varied among environmental and experimental contexts. In experimental populations, thermal regimes alone had little effect on recombination; instead, adaptation to laboratory conditions and specific stressors drove recombination changes. Exposure to microplastics led to a genome-wide reduction in recombination, likely due to stress-induced DNA repair prioritizing genome integrity, whereas cadmium exposure generally suppressed recombination. Our results demonstrate that recombination in C. riparius is a highly dynamic trait influenced by environmental conditions, selection, and genomic context. By integrating ecological variation, experimental evolution, and multivariate genomic analyses, this study highlights recombination as a context-dependent process that responds to both natural and anthropogenic stressors and interacts with multiple features of genome architecture.

Peroxisomes are essential organelles for plant development and stress adaptation, yet the Peroxin11 (PEX11) gene family that mediates peroxisome proliferation remains uncharacterized in wheat (Triticum aestivum L.), a key polyploid cereal. This study presents the first comprehensive genome-wide identification and integrative analysis of the wheat PEX11 genes (TaPEX11), identifying 12 loci encoding 13 protein isoforms due to alternative splicing at one locus. Chromosomal mapping revealed uneven distribution, while protein analyses confirmed a conserved Pfam05648 domain with multiple transmembrane helices; some TaPEX11 members showed divergent features suggestive of specialized roles. Phylogenetic and synteny analyses indicated family expansion through segmental duplications under strong purifying selection. Promoter analysis uncovered diverse cis‑elements associated with hormone signalling, development, and abiotic stress responses. Using RNA‑seq data and qRT‑PCR, I demonstrate that distinct TaPEX11 genes are inducible under drought, with higher expression in the tolerant genotype Masr‑3 compared to the sensitive Sakha‑94. This transcriptional response was associated with increased catalase activity and indicators of oxidative stress response in Masr‑3. Co‑expression network and Gene Ontology analyses linked TaPEX11 genes to photosynthesis, gluconeogenesis, and peroxisomal homeostasis. Overall, the findings highlight the evolutionary diversification and genotype‑specific regulation of wheat PEX11 genes under drought and provides candidates genes and regulatory elements for future functional studies and breeding programs targeting drought tolerance.