GPBees

1/5: New in GPB! How to efficiently build the tree of life for prokaryotes? Zuo introduces WebCVTree4, an alignment-free web server for whole-genome phylogeny and taxonomy, integrating 220k+ genomes. Read: doi.org/10.1093/gpbj... #Phylogeny #Bioinformatics

4/5: The platform features an interactive front-end. Users can configure projects, upload genomes, dynamically adjust tree layouts, and export publication-ready figures or distance matrices for further analysis. #DataScience

5/5: WebCVTree4 provides a comprehensive, user-friendly platform for microbial evolution and taxonomy in the big-data era. It is freely accessible at: cvtree.online Read: doi.org/10.1093/gpbj... #Phylogenetics #WebServer

2/5: It uses the CVTree method, extracting k-mer vectors from whole genomes to bypass heavy sequence alignment. This enables fast and accurate tree reconstruction for tens of thousands of species. #Microbiology #Genomics

3/5: A major upgrade is the CLTree algorithm. It leverages taxonomy to rapidly root unrooted trees, annotate nodes, and systematically evaluate the monophyly of taxa, bridging statistical phylogeny and classical taxonomy. #Evolution

doi.orgscReGAT: Leveraging Knowledge of Regulatory Interactions to Predict Long-range Gene Regulation at Single-cell ResolutionAbstract. Understanding gene regulation at single-cell resolution is crucial for unraveling development, disease, and cellular identity. We introduce singl

1/5: New in GPB! How to decode long-range gene regulation at single-cell resolution? Wen et al. introduce scReGAT, a deep learning framework integrating prior knowledge to reconstruct cell-specific networks. Read: doi.org/10.1093/gpbj... #scRNAseq #DeepLearning

4/5: scReGAT uncovers dynamic regulatory rewiring in neuroblastoma and osteogenic differentiation. Its scores can anticipate transcriptional transitions, revealing early upstream events guiding cell fate. #CancerResearch

scReGAT offers a robust framework for decoding gene regulation and complex disease genetics. Code: github.com/TianLab-Bioi... Read: doi.org/10.1093/gpbj... #Bioinformatics

2/5: scReGAT builds a knowledge-guided regulatory graph using validated cRE-gene and TF-gene interactions. A Graph Attention Network (GAT) then predicts gene expression and assigns interpretable regulatory scores to each edge. #GeneRegulation

3/5: Benchmarked on five datasets, it outperforms existing methods like LINGER. By integrating GWAS loci for Alzheimer's, MS, and schizophrenia, it links non-coding variants to disease-relevant cell types. #GWAS

doi.orgDNA Methylation in Sex Chromosomes and Genes under Selection Underpins Sexual Size DimorphismAbstract. Sexual size dimorphism (SSD) refers to the differences in body size between males and females. Epigenetic mechanisms, such as DNA methylation, ca

1/5: New in GPB! How does DNA methylation drive sexual size dimorphism (SSD)? Wang et al. reveal the spatiotemporal methylome of Chinese tongue sole, showing how methylation regulates growth and evolution. Read: doi.org/10.1093/gpbj... #DNAMethylation #Genomics #Evolution

4/5: Evolutionarily, rapidly evolving genes in this species show lower methylation levels than background genes. This suggests DNA methylation plays a key role in natural selection, helping organisms allocate resources between growth and reproduction. #EvolutionaryBiology

5/5: This study provides the first comprehensive multi-tissue, multi-stage methylome atlas for vertebrate SSD, offering new insights into phenotypic evolution and resource allocation. Read: doi.org/10.1093/gpbj... #DNAMethylation #SSD

2/5: Using WGBS & RNA-seq across 3 life stages and 4 tissues, they found females have lower methylation levels. Sex-dimorphic DMRs increase over the lifetime, mirroring the phenotypic growth divergence between sexes. #Epigenetics #SSD

3/5: Key genes in the GH/IGF and HPG axes are methylated in a sex-specific way. Notably, the female-specific W chromosome is hypermethylated, silencing growth-inhibiting genes more than Z homologs, which may explain the larger female size. #Genomics

doi.orgIntegrating Genomic Studies into Large Birth CohortsAbstract. Adverse exposures during early life, including environmental and genetic factors, can have profound and long-lasting effects on health in later l

1/5: New in GPB! He et al. explore integrating genomics into large birth cohorts to uncover early-life environmental and genetic impacts on maternal and child health. Read: doi.org/10.1093/gpbj... #Genomics #BirthCohort

4/5: Challenges remain: ethical/privacy concerns, complex data integration, delayed clinical translation, loss to follow-up, and scarce multigenerational sampling. Global collaboration is needed. #Genomics #DOHaD

5/5: Large birth cohorts are key to decoding DOHaD. Integrating genomics, multi-omics, and AI will advance maternal and child health and precision prevention. Read: doi.org/10.1093/gpbj... #PrecisionHealth

2/5: The study highlights GWAS with mother-fetal pairs, age-specific genetic effects, and intergenerational Mendelian randomization to separate maternal exposures from offspring genetics. #Genomics #MaternalHealth

3/5: To tackle complex multimodal data, it emphasizes multi-omics and AI. CNNs, Transformers, and GNNs help capture long-range regulatory interactions and build causal inference frameworks across the maternal-fetal axis. #AI #MultiOmics

doi.orgSPAE: Deciphering Cell Cycle Dynamics and Cell States in Single-cell RNA-seq DataAbstract. Rapid advances in single-cell RNA sequencing (scRNA-seq) technology have enabled the investigation of gene expression changes at the single-cell

1/5: New in GPB! Can we better decode cell cycle dynamics from single-cell RNA-seq data? Yi et al. introduce SPAE, an autoencoder-based framework for accurately characterizing cell cycle progression and cellular states. Read more: doi.org/10.1093/gpbj...

4/5: Beyond cell cycle characterization, SPAE enables accurate prediction of cancer cell cycle transitions and effective removal of cell cycle effects from gene expression data. This helps disentangle cell cycle variation from other biological signals.

github.comGitHub - YaJahn/SPAEContribute to YaJahn/SPAE development by creating an account on GitHub.

5/5: SPAE provides a computational framework for investigating cell cycle dynamics, cellular states, and transcriptional heterogeneity in scRNA-seq data. Code available for non-commercial use: github.com/YaJahn/SPAE #scRNAseq #CellCycle #ComputationalBiology

2/5: SPAE (Sinusoidal and Piecewise AutoEncoder) integrates an autoencoder with piecewise linear modeling to capture subtle cell cycle dynamics and distinguish cell states in scRNA-seq data. A new computational approach to studying cellular heterogeneity!

3/5: Compared with existing methods, SPAE demonstrates substantially improved accuracy and robustness in characterizing cell cycle dynamics. It provides a powerful approach for reconstructing cell cycle progression and estimating cell cycle pseudotime.

doi.orgMulti-layer Cis-molQTLs Reveal Regulatory Architecture and Enhance Heritability Explanation for Complex Traits in CattleAbstract. Genome-wide association study (GWAS) analyses have identified numerous loci associated with economic traits in cattle. Many of these loci reside

1/5: New in GPB! Qiu et al. reveal how integrating four layers of cis-molQTLs improves heritability explanation and genomic prediction for economically important traits. Read more: doi.org/10.1093/gpbj... #Genomics #Cattle

4/5: Using 1,788 Huaxi cattle, the researchers show that multi-layer cis-molQTL SNPs collectively explain 61.9% of total SNP-based heritability across 19 complex traits. This highlights the contribution of regulatory variation to complex trait architecture.

5/5: Incorporating cis-molQTL annotations into genomic prediction models improves prediction accuracy for most traits, with a mean gain of 0.05 over conventional GBLUP. These findings provide a framework for informed genomic prediction and precision cattle breeding.

2/5: By integrating 657 RNA-seq libraries from 275 Huaxi cattle with ~10 million SNPs, the study systematically maps four regulatory layers: Gene expression (eQTLs), splicing (sQTLs), alternative polyadenylation (aQTLs), and RNA editing (edQTLs).

3/5: These cis-molQTLs exhibit distinct genomic distributions and functional enrichments, yet collectively contribute to complex trait regulatory networks. Importantly, they are enriched near loci associated with growth, carcass, and meat quality traits.

doi.orgSingle-cell Atlas Reveals Myelopoietic Bias and Immunosuppressive Reprogramming in Metastatic Bone Marrow Across CancersAbstract. Bone metastasis can remodel the bone marrow microenvironment, yet how metastatic tumors reshape hematopoiesis and immunity across marrow regions

1/5: New in GPB! How does bone metastasis reshape hematopoiesis and immunity? A cross-cancer single-cell atlas of 126,986 cells reveals profound remodeling of the metastatic bone marrow ecosystem. Read the study: doi.org/10.1093/gpbj... #BoneMetastasis #SingleCell

4/5: An immunosuppressive ecosystem Metastatic marrow exhibits progressive T/B-cell depletion and enrichment of exhausted or stressed T cells at tumor sites. Altered LGALS9-HAVCR2 and CLEC2-KLRB1 interactions may contribute to local immune dysfunction.

5/5: Beyond immune cells Attenuated CXCL12-CXCR4 and ICAM1-SPN signaling, together with a marrow-specific tumor metaprogram involving IGFBP3/NAMPT, points to disruption of hematopoietic niche support. #CancerResearch #TumorMicroenvironment

2/5: Mapping the metastatic marrow Integrating tumor, involved, and distal bone marrow from liver, prostate, and kidney cancers, alongside benign controls, researchers identified 7 major cell lineages and 66 subpopulations, revealing spatially distinct cellular remodeling.

3/5: Hematopoiesis reprogrammed Bone metastasis shifts myelopoiesis toward immunosuppressive monocyte/macrophage states, with lineage bias emerging at the GMP stage. Meanwhile, erythropoiesis and B lymphopoiesis are impaired by myeloid-like reprogramming of precursors.

doi.orgHypoxia Response Is Associated with Reduced HPV Activity and Tumor Microenvironment Remodeling in Cervical CancerAbstract. Human papillomavirus (HPV) significantly influences cervical cancer progression and treatment, yet its interactions with the tumor microenvironme

1/8: New in GPB! Single-cell and spatial transcriptomics reveal that hypoxia is associated with reduced HPV16 activity, enhanced MHC-I expression, and tumor microenvironment remodeling in cervical cancer. 🔗 doi.org/10.1093/gpbj... #CervicalCancer #HPV

7/8: A hypoxic environment was correlated with the downregulation of E5 activity and elevated MHC-I expression, which may contribute to stronger interactions between hypoxic cancer cells and cytotoxic CD8⁺ T cells.

8/8: Additionally, HPV16 integration in host cells was associated with increased fatty acid metabolism. These findings suggest that combining anti-angiogenic drugs and fatty acid metabolism inhibitors has the potential to improve cervical cancer treatment.

5/8: E5 transcriptional activity was negatively associated with the host interferon response, indicating a role in immune evasion.

6/8: A hypoxic environment was correlated with the downregulation of E5 activity and elevated MHC-I expression, which may contribute to stronger interactions between hypoxic cancer cells and cytotoxic CD8⁺ T cells.

3/8: We performed single-cell and spatial transcriptomic sequencing on cervical cancer samples to explore these interactions.

4/8: By aligning sequencing reads to a merged HPV16-human reference genome, we characterized HPV16 heterogeneity and its association with host states at the single-cell and single-gene levels.

2/8: Human papillomavirus (HPV) significantly influences cervical cancer progression and treatment, yet its interactions with the tumor microenvironment remain incompletely understood.

academic.oup.comValidate User

👏👏 Excited to see HOSCA, the Human Ocular Single-Cell Atlas, now published in Genomics, Proteomics & Bioinformatics. Paper: academic.oup.com/gpb/advance-...

HOSCA integrates >3.88 million single-cell transcriptomes from 704 human samples across 16 ocular regions and 15 diseases, providing a powerful resource for exploring cellular heterogeneity across the human eye.