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Biomedical subjects

Rong Li

Publications and source records attributed to Rong Li.

13 recordsLinked to original sources

Integrated Multi-Omics Analysis Reveals the Genetic Basis of Phenotypic Variation in Tibetan Sheep.

Body size is a key economic trait influencing the profitability of farmed animals. This study used genome-wide association studies (GWAS) to identify five single nucleotide polymorphisms (SNPs) significantly associated with body size in the Tibetan sheep population, advancing molecular breeding and providing a basis for genomic selection. These SNPs are located within five candidate genes. SNaPshot validated GWAS results, demonstrating significant correlations between candidate SNPs and body size traits in Tibetan sheep. Concurrently, hematoxylin and eosin staining, alongside muscle fiber analysis, confirmed pronounced morphological differences in muscle tissue between sheep of varying conformation. Therefore, transcriptome and proteomics were performed on the longest dorsi muscle from large and small Tibetan sheep of both sexes. The transcriptome, together with weighted gene co-expression network analysis (WGCNA), identified VEPH1 and PRKG1 as core genes regulating body characteristics in Tibetan sheep through their involvement in the PI3K-Akt signaling pathway and pathways related to fat deposition. The integrative analyses demonstrated significantly different expression of CARNS1 and CRYAB at both transcriptional and protein levels between the muscles of large- and small-sized Tibetan sheep of both sexes, suggesting their importance in body size traits by influencing muscle morphology. This study provides valuable genomic resources that advance sheep genetics research.

GWAS

The first complete mitochondrial genome of Strigea falconis (Digenea: Strigeidae) reveals six tandemly repeated trnE-containing units and provides mt evidence for the non-monophyly of the family Strigeidae.

BACKGROUND: Phylogenetic relationships among members in the order Diplostomida remain contentious, with mitochondrial (mt) and nuclear genomic data often yielding conflicting topologies. A major limitation is the availability of only a few mt genomes from the type genus Strigea, hindering a robust test of the monophyly of the family Strigeidae and the order Diplostomida. RESULTS: The mt genome of S. falconis was completely sequenced for the first time, which was a circular molecule of 16,872 bp in length, encoding the typical set of 36 mt genes and six duplicate tRNA-Glu genes. Notably, there were seven identical and consecutive tandem repeat units each consist of a 169 bp non-coding region followed by a trnE gene in the newly assembled genome. Phylogenomic analyses based on concatenated predicted amino acid sequences of 12 proteins robustly placed S. falconis in the same clade as Apharyngostrigea pipientis. Crucially, the family Strigeidae was not recovered as monophyletic. Instead, two species within Strigeidae, Cardiocephaloides medioconiger and Cotylurus marcogliesei, clustered with representatives of Diplostomidae, providing mt evidence for the paraphyly of Strigeidae under the current sampling. CONCLUSIONS: The newly sequenced mt genome of S. falconis reveals a previously unreported six-copy tandem repeat of trnE-containing units among currently available diplostomoid mt genomes. Phylogenetic analyses based on mt protein-coding genes provide additional mt evidence that the family Strigeidae was not recovered as monophyletic under the present taxon sampling. However, because mt genomes represent a single maternally inherited linkage group, broader taxon sampling, independent nuclear phylogenomic data, and explicit sensitivity analyses will be required to confirm these relationships and guide any formal systematic revision.

Animals

Prospective clinical validation of targeted long-read sequencing for preimplantation genetic testing of α-thalassaemia.

BACKGROUND: Preimplantation genetic testing for monogenic disorders (PGT-M) can prevent transmission of severe α-thalassaemia, but conventional workflows remain limited by family-specific assay design for direct variant detection, dependence on additional family samples for haplotype construction, and labour-intensive multi-step procedures across several platforms. Targeted long-read sequencing-based PGT-M for α-thalassaemia (tlrPGT-α-thal) integrates direct variant detection and haplotype linkage analysis within a single assay, but prospective clinical validation is lacking. METHODS: This prospective clinical study enrolled 103 families at high risk of transmitting α-thalassaemia at a reproductive medicine centre between August 2024 and March 2025. All families underwent blinded parallel analysis using both conventional NGS-based PGT-M (comparator) and tlrPGT-α-thal. RESULTS: In the primary concordance analysis, tlrPGT-α-thal was fully concordant with conventional NGS-based PGT-M (507/507, 100.0%; exact 95% CI, 99.3-100.0). Direct variant detection was successful in 501/507 embryos (98.82%; 95% CI, 97.4-99.6), haplotype linkage was established in 505/507 embryos (99.61%; 95% CI, 98.6-100.0), and one meiotic recombination event was identified. Among 93 families proceeding to embryo transfer, 57 pregnancies underwent invasive prenatal diagnosis, and all were concordant with the corresponding tlrPGT-α-thal results. Of the 26 comparator-inconclusive embryos, tlrPGT-α-thal resolved 6 complex cases, including cases with incomplete pedigrees or insufficient informative SNPs. Among the remaining 20 embryos with HBA-region aneuploidies, genotype and parental origin could be determined in 12. CONCLUSIONS: The findings show that tlrPGT-α-thal enables direct detection of diverse α-thalassaemia-causing variants together with efficient haplotype linkage analysis within a single workflow, without requiring family-specific assay design or additional family samples. The method demonstrated high diagnostic accuracy while providing added value in complex scenarios. Taken together, tlrPGT-α-thal represents a simplified and broadly applicable strategy for α-thalassaemia PGT-M.

Humans

Epigenetic safety of in vitro maturation in PCOS: genome-wide DNA methylation profiling of cord blood from a randomized controlled trial.

BACKGROUND: In vitro maturation (IVM) provides a safer alternative to conventional in vitro fertilization (IVF) for women with polycystic ovary syndrome (PCOS) by mitigating the risk of ovarian hyperstimulation. However, concerns persist regarding whether IVM perturbs epigenetic reprogramming in the offspring. Current evidence is constrained by candidate-gene approaches or a lack of parental controls. This study aimed to evaluate the genome-wide DNA methylation safety of IVM compared with conventional IVF using a rigorous trio-based design. METHODS: This secondary epigenetic analysis was nested within a randomized controlled trial (RCT) (ClinicalTrials.gov: NCT03463772). We included 10 nuclear families (trios), comprising five IVM-conceived and five IVF-conceived singleton offspring alongside their biological parents. Both groups utilized a uniform freeze-only single-blastocyst transfer strategy to minimize hormonal confounding. Genomic DNA from umbilical cord blood (UCB) and parental peripheral blood was analyzed using reduced representation bisulfite sequencing (RRBS). Genome-wide methylation patterns and differentially methylated regions (DMRs) were subsequently compared between the groups. RESULTS: Clinical characteristics were comparable between the IVM and IVF groups. Genome-wide analyses demonstrated high concordance in UCB methylation patterns, revealing no significant differences in global CpG methylation levels or distributions across key genomic features (promoters, CpG islands, and gene bodies). Only three rare DMRs were identified in UCB (representing ~ 0.0001% of the genome), none of which mapped to imprinted or developmentally critical loci. Furthermore, methylation variability remained consistent between the groups. CONCLUSIONS: Our findings provide robust mechanistic evidence supporting the epigenetic safety of IVM. The remarkable stability of the neonatal methylome confirms that specific IVM conditions do not compromise early developmental programming, thereby endorsing IVM as a safe and viable alternative for women with PCOS. TRIAL REGISTRATION: ClinicalTrials.gov registry, NCT03463772. Registered on March 13, 2018.

Humans

scATAnno: Automated Cell Type Annotation for Single-cell ATAC-seq Data.

Recent advances in single-cell epigenomic techniques have increased the demand for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) analysis. One key analytical task is to determine cell type identity based on epigenetic data. Here, we introduce scATAnno, a Python package designed to automatically annotate scATAC-seq data using large-scale scATAC-seq reference atlases. This workflow generates reference atlases from publicly available datasets, enabling accurate cell type annotation by integrating query data with reference atlases without the use of single-cell RNA sequencing (scRNA-seq) data. To enhance annotation accuracy, we incorporated k-nearest neighbors (KNN)-based and weighted distance-based uncertainty scores to effectively detect cell populations within the query data that are distinct from all cell types in the reference data. We compared and benchmarked scATAnno against five other published cell annotation approaches, demonstrating its superior performance across multiple datasets and metrics. We further showcased the utility of scATAnno across multiple datasets, including peripheral blood mononuclear cells (PBMCs), triple-negative breast cancer (TNBC), and basal cell carcinoma (BCC), and demonstrated that scATAnno accurately annotates cell types across diverse biological conditions. Overall, scATAnno is a useful tool for scATAC-seq reference atlas construction and cell type annotation and can facilitate the interpretation of new scATAC-seq datasets in complex biological systems. scATAnno is publicly available at https://scatanno-main.readthedocs.io/.

Single-Cell Analysis

ENTPD3 as a novel regulator of endometrial receptivity: suppressing EMT via the ATP-P2Y2 axis in patients with recurrent implantation failure.

BACKGROUND: Recurrent implantation failure (RIF) remains a major challenge in assisted reproductive technology and is primarily attributed to impaired endometrial receptivity. Despite its clinical significance, the precise mechanisms underlying RIF remain inadequately understood. METHODS: Single-cell RNA sequencing (scRNA-seq) was performed on endometrial samples from patients with RIF and healthy controls during the secretory phase using the 10X Genomics Chromium platform. The expression and localization of ectonucleoside triphosphate diphosphohydrolase 3 (ENTPD3) in the window of implantation (WOI) in the endometrium were examined using real-time quantitative polymerase chain reaction (RT-qPCR), western blotting, and immunohistochemistry (IHC). A mouse model with ENTPD3 overexpression was utilized to assess embryo implantation in vivo, and an in vitro blastocyst adhesion assay was performed to evaluate endometrial receptivity. Additionally, Ishikawa cells were transduced with an ENTPD3 recombinant adenovirus to explore the underlying molecular mechanisms. RESULTS: ENTPD3 expression was significantly upregulated in the endometria of patients with RIF during the WOI, and its apical surface localization in endometrial epithelial cells was confirmed by single-cell data and IHC. Functional studies demonstrated that ENTPD3 overexpression impaired endometrial receptivity by suppressing epithelial-mesenchymal transition (EMT). In vivo, ENTPD3 overexpression markedly reduced endometrial receptivity and inhibited embryo implantation in mice. Consistently, in vitro assays revealed that ENTPD3 overexpression diminished blastocyst adhesion to endometrial epithelial cells. Mechanistically, ENTPD3 hydrolyzes ATP, thereby suppressing EMT via the P2Y2 signaling pathway and ultimately disrupting endometrial receptivity. CONCLUSIONS: Dysregulated ENTPD3 expression contributes to RIF pathogenesis by impairing endometrial receptivity through ATP hydrolysis-mediated suppression of EMT via P2Y2 signaling. These findings highlight ENTPD3 as a potential therapeutic target for improving implantation success in affected patients.

Female

An immune exhaustion signature predicts prognosis and identifies patients with diffuse large B-cell lymphoma (DLBCL) who derive preferential benefit from chimeric antigen receptor (CAR)-T cell therapy.

BACKGROUND: The tumor microenvironment (TME) is a key determinant of prognosis in diffuse large B-cell lymphoma (DLBCL). While T-cell exhaustion is implicated in therapeutic failure, its precise molecular hallmarks and utility for predicting response to modern immunotherapies, such as chimeric antigen receptor (CAR)-T cell therapy, remain unclear. METHODS: We performed an integrative analysis of transcriptomic and clinical data from multiple DLBCL cohorts (The Cancer Genome Atlas [TCGA], GSE181063, GSE10846, GSE248835, GSE182434). We used unsupervised clustering, exploratory analysis of single-cell RNA sequencing data, and the least absolute shrinkage and selection operator for variable selection (LASSO-Cox) regression to characterize the exhausted TME, construct a prognostic model, and evaluate its predictive value for CAR-T cell therapy. The model's dynamic behavior was assessed in a proof-of-concept longitudinal cohort of patients treated with the T-cell-engaging bispecific antibody glofitamab. RESULTS: We identified a "high-exhaustion" subtype associated with significantly poorer overall survival (OS; log-rank P = 0.016). Based on this, we developed a five-gene immune exhaustion-Related Prognostic Score (IERPS) that served as a robust independent predictor of poor OS across multiple cohorts. Critically, in a cohort of 256 relapsed/refractory patients, the IERPS was strongly prognostic for event-free survival (EFS) in the standard-of-care (SOC) arm (HR = 2.02, 95% confidence interval [95% CI]: 1.07-3.81, P = 0.029) but lost prognostic significance in the CAR-T arm (HR = 0.70, 95 % CI: 0.35-1.40, P = 0.314). This significant interaction suggests that CAR-T cell therapy may abrogate the poor prognosis associated with a high IERPS. Biologically, exploratory single-cell analysis (n = 4 samples) defined the high-IERPS state by hallmarks of classical T-cell exhaustion, and a descriptive case study showed the score dynamically tracked clinical response to glofitamab. CONCLUSIONS: A state of active T-cell exhaustion and a suppressive TME drive the adverse immune phenotype in DLBCL. Our IERPS model captures this dysfunctional state, acting as a powerful prognostic tool and, more importantly, as a potential predictive biomarker to identify high-risk patients who appear to overcome their inherently poor prognosis through CAR-T cell therapy.

Biomarkers

Incorporating prior information in gene expression network-based cancer heterogeneity analysis.

Cancer is molecularly heterogeneous, with seemingly similar patients having different molecular landscapes and accordingly different clinical behaviors. In recent studies, gene expression networks have been shown as more effective/informative for cancer heterogeneity analysis than some simpler measures. Gene interconnections can be classified as "direct" and "indirect," where the latter can be caused by shared genomic regulators (such as transcription factors, microRNAs, and other regulatory molecules) and other mechanisms. It has been suggested that incorporating the regulators of gene expressions in network analysis and focusing on the direct interconnections can lead to a deeper understanding of the more essential gene interconnections. Such analysis can be seriously challenged by the large number of parameters (jointly caused by network analysis, incorporation of regulators, and heterogeneity) and often weak signals. To effectively tackle this problem, we propose incorporating prior information contained in the published literature. A key challenge is that such prior information can be partial or even wrong. We develop a two-step procedure that can flexibly accommodate different levels of prior information quality. Simulation demonstrates the effectiveness of the proposed approach and its superiority over relevant competitors. In the analysis of a breast cancer dataset, findings different from the alternatives are made, and the identified sample subgroups have important clinical differences.

Humans

Diagnostic performance of the Sanity 2.0 assay to detect resistance to rifampicin, isoniazid, and fluoroquinolones in tuberculosis.

UNLABELLED: Effective tuberculosis (TB) management relies on prompt diagnosis of Mycobacterium tuberculosis complex (MTBC) and associated drug resistance. The Sanity 2.0 assay is a high-resolution melting assay designed for direct respiratory sample testing, enabling simultaneous detection of MTBC and resistance to rifampicin (RIF), isoniazid (INH), and fluoroquinolones (FQ) in a single step. This study evaluated its diagnostic performance in two registered multicenter trials among bacteriologically confirmed TB patients. Diagnostic performance was evaluated for MTBC detection, as well as for the identification of resistance to RIF, INH, and FQ, using phenotypic drug susceptibility testing, whole-genome sequencing, and a composite reference standard. Agreement analyses were conducted between the Sanity 2.0 assay and Xpert MTB/RIF and Xpert MTB/XDR. Among 611 patients, the Sanity 2.0 assay detected MTBC in 563 patients, exhibiting a sensitivity of 92.1% (95% CI: 89.7-94.0). For detecting resistance to RIF, INH, and FQ, sensitivities exceeded 90%, with specificities of 95.8% (95% CI: 88.5-98.6), 100.0% (95% CI: 96.4-100.0), and 97.8% (95% CI: 93.8-99.3) against the composite reference standard, respectively. The agreement with Xpert MTB/RIF for RIF detection was 98.6% (95% CI: 96.9-99.3). For INH and FQ resistance, the agreement with Xpert MTB/XDR was 92.0% (95% CI: 88.5-94.5) and 94.3% (95% CI: 91.2-96.3), respectively. The Sanity 2.0 assay is a rapid and user-friendly platform capable of detecting both MTBC and key drug resistance. It demonstrated good diagnostic performance and could potentially be an effective alternative to guide individualized anti-TB treatment, especially in resource-limited settings. IMPORTANCE: Rapid and accurate detection of both Mycobacterium tuberculosis complex (MTBC) and key drug resistance is critical to improving tuberculosis treatment outcomes and reducing transmission. However, current molecular diagnostic workflows often require sequential testing, which can delay the initiation of effective and individualized therapy. We evaluated the Sanity 2.0 assay, an integrated high-resolution melting test that simultaneously detects MTBC and resistance to rifampicin, isoniazid, and fluoroquinolone resistance directly from respiratory samples in about 2-3 hours. The assay demonstrated excellent performance, with MTBC detection sensitivity of 92.1% and drug resistance sensitivities exceeding 90% and specificities over 95% against a composite reference standard, as well as strong concordance with World Health Organization-endorsed molecular assays. Implementation of the Sanity 2.0 assay could streamline TB diagnostic workflows; enable rapid, single-step resistance profiling; and facilitate timely, individualized treatment-particularly in resource-limited settings where rapid and comprehensive resistance testing remains a critical unmet need.

Humans

Platelets sequester extracellular DNA, capturing tumor-derived and free fetal DNA.

Platelets are anucleate blood cells vital for hemostasis and immunity. During cell death and aberrant mitosis, nucleated cells release DNA, resulting in "cell-free" DNA in plasma (cfDNA). An excess of cfDNA is deleterious. Given their ability to internalize pathogen-derived nucleic acids, we hypothesized that platelets may also clear endogenous cfDNA. We found that, despite lacking a nucleus, platelets contained a repertoire of DNA fragments mapping across the nuclear genome. We detected fetal DNA in maternal platelets and cancer-derived DNA in platelets from patients with premalignant and cancerous lesions. As current liquid biopsy approaches utilize platelet-depleted plasma, important genetic information contained within platelets is being missed. This study establishes a physiological role for platelets that has not previously been highlighted, with broad translational relevance.

Female

Bayesian Modeling of Cancer Outcomes Using Genetic Variables Assisted by Pathological Imaging Data.

With the increasing maturity of genetic profiling, an essential and routine task in cancer research is to model disease outcomes/phenotypes using genetic variables. Many methods have been successfully developed. However, oftentimes, empirical performance is unsatisfactory because of a "lack of information." In cancer research and clinical practice, a source of information that is broadly available and highly cost-effective comes from pathological images, which are routinely collected for definitive diagnosis and staging. In this article, we consider a Bayesian approach for selecting relevant genetic variables and modeling their relationships with a cancer outcome/phenotype. We propose borrowing information from (manually curated, low-dimensional) pathological imaging features via reinforcing the same selection results for the cancer outcome and imaging features. We further develop a weighting strategy to accommodate the scenario where information borrowing may not be equally effective for all subjects. Computation is carefully examined. Simulations demonstrate competitive performance of the proposed approach. We analyze TCGA (The Cancer Genome Atlas) LUAD (lung adenocarcinoma) data, with overall survival and gene expressions being the outcome and genetic variables, respectively. Findings different from the alternatives and with sound properties are made.

Humans

Modeling early gastrulation in human blastoids with DNA methylation patterns of natural blastocysts.

Blastoids are a promising model for studying early human embryogenesis, but current models have limitations in post-implantation development and lack comprehensive epigenetic assessments, especially regarding genomic imprinting. These issues can lead to failures in accurately modeling early embryonic development. In this study, we developed a high-fidelity blastoid model using 4 chemicals + leukemia inhibitory factor (LIF) (4CL) naive human pluripotent stem cells (hPSCs) (4CL blastoids). 4CL blastoids closely resemble human blastocysts in morphology and transcriptional profiles, exhibiting similar DNA methylation and gene imprinting patterns. By extending the 3D culture to 14 days, these blastoids mimic early gastrulation, demonstrating the specification and migration of cells. They also show the transcriptional signature of hemogenic angioblast (HAB) cells at Carnegie stage 6 (CS6). This model bridges pre- and post-implantation stages, offering valuable insights into early tissue formation and human development.

Humans

Tomato bacterial wilt disease outbreaks are accompanied by an increase in soil antibiotic resistance.

The presence of soil-borne disease obstacles and antibiotic resistance genes (ARGs) in soil leads to serious economic losses and health risks to humans. One area in need of attention is the evolution of ARGs as pathogenic soil gradually develops, which introduces uncertainty to the dynamic ability of conventional farming models to predict ARGs. Here, we investigated variations in tomato bacterial wilt disease accompanied by the resistome by metagenomic analysis in soils over 13 seasons of monoculture. The results showed that the abundance and diversity of ARGs and mobile genetic elements (MGEs) exhibited a significant and positive correlation with R. solanacearum. Furthermore, the binning approach indicated that fluoroquinolone (qepA), tetracycline (tetA), multidrug resistance genes (MDR, mdtA, acrB, mexB, mexE), and β-lactamases (ampC, blaGOB) carried by the pathogen itself were responsible for the increase in overall soil ARGs. The relationships between pathogens and related ARGs that might underlie the breakdown of soil ARGs were further studied in R. solanacearum invasion pot experiments. This study revealed the dynamics of soil ARGs as soil-borne diseases develop, indicating that these ecological trends can be anticipated. Overall, this study enhances our understanding of the factors driving ARGs in disease-causing soils.

Soil Microbiology