A genome-wide association study reveals candidate genes and regulatory regions associated with birth weight in pigs.

Piglet birth weight is associated with preweaning survival, and its related traits have been included in the breeding program. Thus, understanding its genetic basis is essential. This study identified four birth weight-associated genomic regions on chromosomes 2, 4, 5, and 7 through genome-wide association study analysis in 7286 pigs from three different pure breeds using the FarmCPU model. The genetic and phenotypic variance explained by the four candidate regions is 8.42% and 1.85%, respectively. Twenty-eight candidate genes were detected, of which APPL2, TGFBI, MACROH2A1, and SEC22B have been reported to affect body growth or development. In addition, 21 H3K4me3-enriched peaks overlapped with the birth weight-associated genomic regions were identified by integrating the genome-wide association study results with our previous ChIP-seq and RNA-seq data generated in the pig placenta, a fetal organ relevant to birth weight, and three of the regulatory regions influence TGFBI, MACROH2A1, and SEC22B expression. This study provides new insights into understanding the mechanisms for birth weight. Further investigating the variants in the regulatory regions would help identify the functional variants for birth weight in pigs.

Construction of a supramolecular antibacterial material based on water-soluble pillar[5]arene and a zwitterionic guest molecule.

A new antibacterial system (HG) based on the host-guest chemistry between pillar[5]arene and a zwitterionic guest was fabricated. The HG complex displayed excellent antibacterial and biofilm formation inhibition and dispersal activities against E. coli, S. aureus and MRSA.

Antibody-drug conjugates in gastric cancer: from molecular landscape to clinical strategies.

Antibody-drug conjugates (ADCs) represent a crucial component of targeted therapies in gastric cancer, potentially altering traditional treatment paradigms. Many ADCs have entered rigorous clinical trials based on biological theories and preclinical experiments. Modality trials have also been conducted in combination with monoclonal antibody therapies, chemotherapies, immunotherapies, and other treatments to enhance the efficacy of drug coordination effects. However, ADCs exhibit limitations in treating gastric cancer, including resistance triggered by their structure or other factors. Ongoing intensive researches and preclinical experiments are yielding improvements, while enhancements in drug development processes and concomitant diagnostics during the therapeutic period actively boost ADC efficacy. The optimal treatment strategy for gastric cancer patients is continually evolving. This review summarizes the clinical progress of ADCs in treating gastric cancer, analyzes the mechanisms of ADC combination therapies, discusses resistance patterns, and offers a promising outlook for future applications in ADC drug development and companion diagnostics.

Methylation synthetic lethality: Exploiting selective drug targets for cancer therapy.

In cancer, synthetic lethality refers to the drug-induced inactivation of one gene and the inhibition of another in cancer cells by a drug, resulting in the death of only cancer cells; however, this effect is not present in normal cells, leading to targeted killing of cancer cells. Recent intensive epigenetic research has revealed that aberrant epigenetic changes are more frequently observed than gene mutations in certain cancers. Recently, numerous studies have reported various methylation synthetic lethal combinations involving DNA damage repair genes, metabolic pathway genes, and paralogs with significant results in cellular models, some of which have already entered clinical trials with promising results. This review systematically introduces the advantages of methylation synthetic lethality and describes the lethal mechanisms of methylation synthetic lethal combinations that have recently demonstrated success in cellular models. Furthermore, we discuss the future opportunities and challenges of methylation synthetic lethality in targeted anticancer therapies.

Identification and expression profiling of SmGATA genes family involved in response to light and phytohormones in eggplant.

GATA proteins are transcription factors of zinc finger proteins, which play an important role in plant growth development and abiotic stress. However, there have been no identification or systematic studies of the GATA gene family in eggplant. In this study, 28 SmGATA genes were identified in the genome database of eggplant, which could be divided into four subgroups. Plant development, hormones, and stress-related cis-acting elements were identified in promoter regions of the SmGATA gene family. RT-qPCR indicated that 4 SmGATA genes displayed upregulated expressions during fruit developmental stage, whereas 2 SmGATA genes were down-regulated expression patterns. It was also demonstrated that SmGATA genes may be involved in light signals to regulate fruit anthocyanin biosynthesis. Furthermore, the expression patterns of SmGATA genes under ABA, GA and MeJA treatments showed that the SmGATAs were involved in the process of fruit ripening. Notably, SmGATA4 and SmGATA23 were highly correlated with the expression of anthocyanin biosynthesis genes, light-responsive genes, and genes that function in multiple hormone signaling pathways and the proteins they encoded were localized in the nucleus. All these results showed GATA genes likely play a major role in regulating fruit anthocyanin biosynthesis by integrating the light, ABA, GA and MeJA signaling pathways and provided references for further research on fruit quality in eggplant.

Genetic basis of phenotypic convergence in pig terminal sires using pathway-based selection signature detection methods.

The primary purpose of genetic improvement in lean pig breeds is to enhance production performance. Owing to their similar breeding directions, Duroc and Pietrain pigs are ideal models for investigating the phenotypic convergence underlying artificial selection. However, most important economic traits are controlled by a polygenic basis, so traditional strategies for detecting selection signatures may not fully reveal the genetic basis of complex traits. The pathway-based gene network analysis method utilizes each pathway as a unit, overcoming the limitations of traditional strategies for detecting selection signatures by revealing the selection of complex biological processes. Here, we utilized 13 122 398 high-quality SNPs from whole-genome sequencing data of 48 Pietrain pigs, 156 Duroc pigs and 36 European wild boars to detect selective signatures. After calculating FST and iHS scores, we integrated the pathway information and utilized the r/bioconductor graphite and signet packages to construct gene networks, identify subnets and uncover candidate genes underlying selection. Using the traditional strategy, a total of 47 genomic regions exhibiting parallel selection were identified. The enriched genes, including INO80, FZR1, LEPR and FAF1, may be associated with reproduction, fat deposition and skeletal development. Using the pathway-based selection signatures detection method, we identified two significant biological pathways and eight potential candidate genes underlying parallel selection, such as VTN, FN1 and ITGAV. This study presents a novel strategy for investigating the genetic basis of complex traits and elucidating the phenotypic convergence underlying artificial selection, by integrating traditional selection signature methods with pathway-based gene network analysis.

Corrigendum: Assessing causal associations between neurodegenerative diseases and neurological tumors with biological aging: a bidirectional Mendelian randomization study.

[This corrects the article DOI: 10.3389/fnins.2023.1321246.].

Establishment and application of a root wounding-immersion method for efficient virus-induced gene silencing in plants.

In the post-genomic era, virus-induced gene silencing (VIGS) has played an important role in research on reverse genetics in plants. Commonly used Agrobacterium-mediated VIGS inoculation methods include stem scratching, leaf infiltration, use of agrodrench, and air-brush spraying. In this study, we developed a root wounding-immersion method in which 1/3 of the plant root (length) was cut and immersed in a tobacco rattle virus (TRV)1:TRV2 mixed solution for 30 min. We optimized the procedure in Nicotiana benthamiana and successfully silenced N. benthamiana, tomato (Solanum lycopersicum), pepper (Capsicum annuum L.), eggplant (Solanum melongena), and Arabidopsis thaliana phytoene desaturase (PDS), and we observed the movement of green fluorescent protein (GFP) from the roots to the stem and leaves. The silencing rate of PDS in N. benthamiana and tomato was 95-100%. In addition, we successfully silenced two disease-resistance genes, SITL5 and SITL6, to decrease disease resistance in tomatoes (CLN2037E). The root wounding-immersion method can be used to inoculate large batches of plants in a short time and with high efficiency, and fresh bacterial infusions can be reused several times. The most important aspect of the root wounding-immersion method is its application to plant species susceptible to root inoculation, as well as its ability to inoculate seedlings from early growth stages. This method offers a means to conduct large-scale functional genome screening in plants.

Single-Cell RNA-Sequencing Reveals Heterogeneity and Transcriptional Dynamics in Porcine Circulating CD8+ T Cells.

Pigs are the most important source of meat and valuable biomedical models. However, the porcine immune system, especially the heterogeneity of CD8 T cell subtypes, has not been fully characterized. Here, using single-cell RNA sequencing, we identified 14 major cell types from peripheral blood circulating cells of pigs and observed remarkable heterogeneity among CD8 T cell types. Upon re-clustering of CD8+ T cells, we defined four CD8 T cell subtypes and revealed their potential differentiation trajectories and transcriptomic differences among them. Additionally, we identified transcription factors with potential regulatory roles in maintaining CD8 T cell differentiation. The cell-cell communication analysis inferred an extensive interaction between CD8 T cells and other immune cells. Finally, cross-species analysis further identified species-specific and conserved cell types across different species. Overall, our study provides the first insight into the extensive functional heterogeneity and state transitions among porcine CD8 T cell subtypes in pig peripheral blood, complements the knowledge of porcine immunity, and enhances its potential as a biomedical model.

Tumor microenvironment characteristics and prognostic role of m6A modification in lung squamous cell carcinoma.

Background: It has recently been determined that N6-methyladenosine (m6A) RNA methylation regulators have prominent effects on several cancers. However, the potential role of m6A modification in lung squamous cell carcinoma (LUSC) remains unclear. Methods: We evaluated the modification pattern of m6A and studied the biological function of m6A regulators in LUSC. Then, we constructed the m6Ascore to predict the prognosis of LUSC and analyzed the relationship between the m6Ascore and tumor mutation burden, immune cell infiltration, and immunotherapy. Result: In the unsupervised consensus cluster analysis, three different m6Aclusters were identified, which correspond to an immune activation state, a moderate immune activation state, and an immune tolerance state. Forty-two genes related to the m6A phenotype were used to construct the m6Ascore; subsequently, multiple validations of the m6Ascore were carried out to determine the relationship between the score and immune cell infiltration and response to CTLA-4/PD-1 inhibitor treatment. Further analysis revealed that the m6Ascore could effectively predict the prognosis of LUSC and that the m6A phenotype-related genes, FAM162A and LOM4, might be potential biomarkers. Conclusion: These findings highlight the potential role of m6A modification in the prognosis, TME, and immunotherapy of LUSC and have profound implications for developing more effective personalized treatment strategies for LUSC.

Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations.

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform "N-of-1" analyses on individual patients. The increasing sizes of ultra-rare, "N-of-1" disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development.1,2 The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale N-of-1 analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We apply existing and introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We make our gene-level findings and variant-level information across the cohort available in a public-facing browser (https://dbmi-bgm.github.io/udn-browser/). These results show that N-of-1 efforts should be supplemented by a joint genomic analysis across cohorts.

Comparative transcriptome analysis of T lymphocyte subpopulations and identification of critical regulators defining porcine thymocyte identity.

Introduction: The development and migration of T cells in the thymus and peripheral tissues are crucial for maintaining adaptive immunity in mammals. However, the regulatory mechanisms underlying T cell development and thymocyte identity formation in pigs remain largely underexplored. Method: Here, by integrating bulk and single-cell RNA-sequencing data, we investigated regulatory signatures of porcine thymus and lymph node T cells. Results: The comparison of T cell subpopulations derived from porcine thymus and lymph nodes revealed that their transcriptomic differences were influenced more by tissue origin than by T cell phenotypes, and that lymph node cells exhibited greater transcriptional diversity than thymocytes. Through weighted gene co-expression network analysis (WGCNA), we identified the key modules and candidate hub genes regulating the heterogeneity of T cell subpopulations. Further, we integrated the porcine thymocyte dataset with peripheral blood mononuclear cell (PBMC) dataset to systematically compare transcriptomic differences between T cell types from different tissues. Based on single-cell datasets, we further identified the key transcription factors (TFs) responsible for maintaining porcine thymocyte identity and unveiled that these TFs coordinately regulated the entire T cell development process. Finally, we performed GWAS of cell type-specific differentially expressed genes (DEGs) and 30 complex traits, and found that the DEGs in thymus-related and peripheral blood-related cell types, especially CD4_SP cluster and CD8-related cluster, were significantly associated with pig productive and reproductive traits. Discussion: Our findings provide an insight into T cell development and lay a foundation for further exploring the porcine immune system and genetic mechanisms underlying complex traits in pigs.

A Novel Approach Utilizing Domain Adversarial Neural Networks for the Detection and Classification of Selective Sweeps.

The identification and classification of selective sweeps are of great significance for improving the understanding of biological evolution and exploring opportunities for precision medicine and genetic improvement. Here, a domain adaptation sweep detection and classification (DASDC) method is presented to balance the alignment of two domains and the classification performance through a domain-adversarial neural network and its adversarial learning modules. DASDC effectively addresses the issue of mismatch between training data and real genomic data in deep learning models, leading to a significant improvement in its generalization capability, prediction robustness, and accuracy. The DASDC method demonstrates improved identification performance compared to existing methods and excels in classification performance, particularly in scenarios where there is a mismatch between application data and training data. The successful implementation of DASDC in real data of three distinct species highlights its potential as a useful tool for identifying crucial functional genes and investigating adaptive evolutionary mechanisms, particularly with the increasing availability of genomic data.

Hi-Tag: a simple and efficient method for identifying protein-mediated long-range chromatin interactions with low cell numbers.

Protein-mediated chromatin interactions can be revealed by coupling proximity-based ligation with chromatin immunoprecipitation. However, these techniques require complex experimental procedures and millions of cells per experiment, which limits their widespread application in life science research. Here, we develop a novel method, Hi-Tag, that identifies high-resolution, long-range chromatin interactions through transposase tagmentation and chromatin proximity ligation (with a phosphorothioate-modified linker). Hi-Tag can be implemented using as few as 100,000 cells, involving simple experimental procedures that can be completed within 1.5 days. Meanwhile, Hi-Tag is capable of using its own data to identify the binding sites of specific proteins, based on which, it can acquire accurate interaction information. Our results suggest that Hi-Tag has great potential for advancing chromatin interaction studies, particularly in the context of limited cell availability.

Sprayable Zwitterionic Antibacterial Hydrogel With High Mechanical Resilience and Robust Adhesion for Joint Wound Treatment.

Wound healing in movable parts, including the joints and neck, remains a critical challenge due to frequent motions and poor flexibility of dressings, which may lead to mismatching of mechanical properties and poor fitting between dressings and wounds; thus, increasing the risk of bacterial infection. This study proposes a sprayable zwitterionic antibacterial hydrogel with outstanding flexibility and desirable adhesion. This hydrogel precursor is fabricated by combining zwitterionic sulfobetaine methacrylate (SBMA) with poly(sulfobetaine methacrylate-co-dopamine methacrylamide)-modified silver nanoparticles (PSBDA@AgNPs) through robust electrostatic interactions. About 150 s of exposure to UV light, the SBMA monomer polymerizes to form PSB chains entangled with PSBDA@AgNPs, transformed into a stable and adhesion PSB-PSB@Ag hydrogel at the wound site. The resulting hydrogel has adhesive strength (15-38 kPa), large tensile strain (>400%), suitable shape adaptation, and excellent mechanical resilience. Moreover, the hydrogel displays pH-responsive behavior; the acidic microenvironment at the infected wound sites prompts the hydrogel to rapidly release AgNPs and kill bacteria. Further, the healing effect of the hydrogel is demonstrated on the rat neck skin wound, showing improved wound closing rate due to reduced inflammation and enhanced angiogenesis. Overall, the sprayable zwitterionic antibacterial hydrogel has significant potential to promote joint skin wound healing.

Injectable hydrogel with antimicrobial and anti-inflammatory properties for postoperative tumor wound care.

Clinically, tumor removal surgery leaves irregularly shaped wounds that are susceptible to bacterial infection and further lead to excessive inflammation. Injectable hydrogel dressings with antimicrobial and anti-inflammatory properties have been recognized as an effective strategy to care for postoperative tumor wounds and prevent recurrence in recent years. In this work, we constructed a hydrogel network by ionic bonding interactions between quaternized chitosan (QCS) and epigallocatechin gallate (EGCG)-Zn complexes which were coordinated by EGCG and zinc ions. Because of the synergistic effect of QCS and EGCG-Zn, the hydrogel exhibited outstanding antimicrobial capacity (>99.9% inhibition), which could prevent infections caused byEscherichia coli and Staphylococcus aureus. In addition, the hydrogel was able to inhibit the growth of mice breast cancer cells (56.81% survival rate within 72 h) and reduce inflammation, which was attributed to the sustained release of EGCG. The results showed that the hydrogel was effective in inhibiting tumor recurrence and accelerating wound closure when applied to the postoperative tumor wounds. This study provided a simple and reliable strategy for postoperative tumor wound care using antimicrobial and anti-inflammatory injectable dressings, confirming their great potential in the field of postoperative wound dressings.

AGIDB: a versatile database for genotype imputation and variant decoding across species.

The high cost of large-scale, high-coverage whole-genome sequencing has limited its application in genomics and genetics research. The common approach has been to impute whole-genome sequence variants obtained from a few individuals for a larger population of interest individually genotyped using SNP chip. An alternative involves low-coverage whole-genome sequencing (lcWGS) of all individuals in the larger population, followed by imputation to sequence resolution. To overcome limitations of processing lcWGS data and meeting specific genotype imputation requirements, we developed AGIDB (https://agidb.pro), a website comprising tools and database with an unprecedented sample size and comprehensive variant decoding for animals. AGIDB integrates whole-genome sequencing and chip data from 17 360 and 174 945 individuals, respectively, across 89 species to identify over one billion variants, totaling a massive 688.57 TB of processed data. AGIDB focuses on integrating multiple genotype imputation scenarios. It also provides user-friendly searching and data analysis modules that enable comprehensive annotation of genetic variants for specific populations. To meet a wide range of research requirements, AGIDB offers downloadable reference panels for each species in addition to its extensive dataset, variant decoding and utility tools. We hope that AGIDB will become a key foundational resource in genetics and breeding, providing robust support to researchers.

Metallic-Polyphenolic Nanoparticles Reinforced Cationic Guar Gum Hydrogel for Effectively Treating Burn Wound.

The development of injectable hydrogel dressings which are long-term moisturizing, easy-to-apply, and effectively inhibiting infection and inflammatory is essential to promote burn wound repairing. Herein, an injectable hydrogel with moisturizing, antibacterial, and anti-inflammation abilities via multiple reversible interactions between cation guar gum (CG) and metallic-polyphenolic nanoparticles (PA-ZnII NPs) is developed. Specifically, PA-ZnII NPs is formed by synergistic complexation of protocatechualdehyde (PA) and zinc ion (Zn2+ ), provides CGPZ hydrogel with plentiful reversible interactions to inhibit the loss of moist. By interacting with PA-ZnII NPs, the CGPZ hydrogel can provide enhanced moisturization for more than 3 days. Moreover, the CGPZ hydrogel can maintain good adhesion for a period of time with injection and self-healing capabilities due to reversible interactions between CG and PA-ZnII NPs. In addition, CGPZ hydrogel exhibits outstanding broad spectrum antibacterial performance, as its killing efficiency against Escherichia coli and Staphylococcus aureus is all greater than 99.99%. Importantly, compared with commercial dressing, the CGPZ hydrogel can promote wound healing faster by inhibiting tissue damage from dysregulated inflammation and accelerating neovascularization. It is believed that the moisturizing CGPZ hydrogel with antibacterial and anti-inflammation performance can serve as a promising dressing for the effective treatment of burn wound.

Characterizing structural variants based on graph-genotyping provides insights into pig domestication and local adaption.

Structural variants (SVs), such as deletions (DELs) and insertions (INSs), contribute substantially to pig genetic diversity and phenotypic variation. Using a library of SVs discovered from long-read primary assemblies and short-read sequenced genomes, we map pig genomic SVs with a graph-based method for re-genotyping SVs in 402 genomes. Our results demonstrate that those SVs harboring specific trait-associated genes may greatly shape pig domestication and local adaptation. Further characterization of SVs reveals that some population-stratified SVs may alter the transcription of genes by affecting regulatory elements. We identify that the genotypes of two DELs (296-bp DEL, chr7: 52,172,101-52,172,397; 278-bp DEL, chr18: 23,840,143-23,840,421) located in muscle-specific enhancers are associated with the expression of target genes related to meat quality (FSD2) and muscle fiber hypertrophy (LMOD2 and WASL) in pigs. Our results highlight the role of SVs in domestic porcine evolution, and the identified candidate functional genes and SVs are valuable resources for future genomic research and breeding programs in pigs.

Pathological Features and Genetic Polymorphism Analysis of Tomato Spotted Wilt Virus in Infected Tomato Fruit.

An in-house tomato inbred line, YNAU335, was planted in a greenhouse in spring from 2014 to 2017, and showed immunity to tomato spotted wilt virus (TSWV). YNAU335 was infected with TSWV in the spring from 2018 to 2020, and disease was observed on the leaves, sepals, and fruits. In 2021 and 2022, YNAU335 was planted in spring in the same greenhouse, which was suspected of being infected with TSWV, and visible disease symptoms were observed on the fruits. Transmission electron microscopy, deep sequencing of small RNAs, and molecular mutation diagnosis were used to analyze the pathological features and genetic polymorphism of TSWV infecting tomato fruit. Typical TSWV virions were observed in the infected fruits, but not leaves from YNAU335 grown between 2021 and 2022, and cross-infection was very rarely observed. The number of mitochondria and chloroplasts increased, but the damage to the mitochondria was greater than that seen in the chloroplasts. Small RNA deep sequencing revealed the presence of multiple viral species in TSWV-infected and non-infected tomato samples grown between 2014-2022. Many virus species, including TSWV, which accounted for the largest proportion, were detected in the TSWV-infected tomato leaves and fruit. However, a variety of viruses other than TSWV were also detected in the non-infected tissues. The amino acids of TSWV nucleocapsid proteins (NPs) and movement proteins (MPs) from diseased fruits of YNAU335 picked in 2021-2022 were found to be very diverse. Compared with previously identified NPs and MPs from TSWV isolates, those found in this study could be divided into three types: non-resistance-breaking, resistance-breaking, and other isolates. The number of positive clones and a comparison with previously identified amino acid mutations suggested that mutation F at AA118 of the MP (GenBank OL310707) is likely the key to breaking the resistance to TSWV, and this mutation developed only in the infected fruit of YNAU335 grown in 2021 and 2022.