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Yang, Y.-C.

Publications and source records attributed to Yang, Y.-C..

11 recordsLinked to original sources

Comparative genomics of a poinsettia-associated phytoplasma and functional validation of its SAP11-homologous effectors that induce plant branching

Phytoplasmas are insect-transmitted plant pathogens that manipulate host development through secreted effector proteins. While they are notorious for causing agricultural losses, in the ornamental plant poinsettia (Euphorbia pulcherrima), phytoplasma infection is uniquely harnessed to induce the commercially desirable free-branching trait. However, the effectors responsible for this phenotype have remained unknown. To address this question, we sequenced and analyzed the genome of Candidatus Phytoplasma pruni PR2021, a strain associated with the high-branching cultivar Princettia Pink. Comparative genomics confirmed its species assignment and revealed an unusual effector repertoire. PR2021 lacks most previously described effectors but encodes two distinct SAP11 homologs, a family of effectors known to induce plant branching. Genomic context analysis showed that one homolog is located within a potential mobile unit (PMU) and is nearly identical to the SAP11 of the distantly related Ca. P. asteris, while the other is located outside PMU regions and is divergent in sequence and predicted structure. Functional assays using Agrobacterium-mediated transient expression in Nicotiana benthamiana demonstrated that each homolog independently induced significant branching, whereas co-expression did not enhance the phenotype, indicating overlapping functions. These findings establish a direct connection between poinsettia branching and SAP11-homologous effectors, providing the first experimental evidence linking phytoplasma effector activity to this horticulturally important trait. This work expands understanding of phytoplasma effector diversity and mobility, while offering a functional framework for developing pathogen-free strategies to modulate ornamental plant architecture. IMPACT STATEMENTPhytoplasmas are uncultivated bacterial pathogens that reprogram host development through secreted effectors. While they are notorious for causing agricultural losses, phytoplasma infection is uniquely harnessed to induce the desirable free-branching trait in poinsettia, although the molecular basis has remained unresolved. Through analysis of the complete genome of Candidatus Phytoplasma pruni PR2021, a strain associated with a high-branching cultivar, we identified two SAP11-homologous effectors with contrasting genomic and evolutionary contexts. One appears vertically inherited and divergent from previously characterized homologs, whereas the other is embedded in a potential mobile unit and likely acquired through horizontal transfer. Importantly, both homologs induce branching despite substantial sequence divergence. Taken together, this work advances understanding of phytoplasma genome evolution and effector diversity, while providing experimental evidence that links effector function to host developmental manipulation. Beyond its horticultural relevance, it illustrates how horizontal gene transfer and lineage-specific retention shape phytoplasma effector complements, offering a foundation for future efforts to dissect and re-engineer effector-host interactions. DATA SUMMARYAll genome assemblies analyzed in this study were obtained from the National Center for Biotechnology Information (NCBI) Genome Database. The accession numbers are provided in Table S1.

genomics↗

deCYPher: Star Allele-Resolution Computational Framework of Pharmacogenes for Haplotype-Resolved Long-Read Assemblies

Although existing next-generation sequencing (NGS) tools, such as Aldy and Cyrius, have been applied for allele typing, they cannot achieve complete accuracy due to various genomic challenges including pseudogenes, structural variations, hybrid genes, copy number variations, and gene deletions. These complexities make accurate pharmacogene interpretation more challenging, despite the crucial role pharmacogenomics plays in precision medicine. We developed deCYPher, a tool that generates personalized pharmacogenomic reports from haplotype-resolved assemblies. The tool enables analysis of all PharmVar 1A level genes, such as CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5, CYP4F2, DPYD, NUDT15, and SLCO1B1. Applied to all HPRC haplotypes (including both release 1 and release 2 data), deCYPher demonstrated high accuracy in resolving complex gene structures. In the case of CYP2D6, release 1 identified 6% gene multiplications, 6% full gene deletions, and 4% CYP2D6/CYP2D7 hybrids. By contrast, release 2 demonstrated an increased prevalence of multiplications (14%) and hybrids (11%), while the frequency of full gene deletions remained comparable at 5%. Comparison with pb-StarPhase revealed discrepancies in 12 of 94 assemblies in the release 1 dataset. For instance, in sample HG02257, Aldy, Cyrius, and deCYPher consistently identified the genotype as *2/*35, whereas pb-StarPhase reported *2/*2. Notably, the *35-defining variants were present in the BAM and VCF files in the pb-StarPhase pipeline, but the local read depth over the *35-specific region was only 5x in HG02257-p, suggesting that the misclassification likely resulted from insufficient coverage - a known limitation of pb-StarPhase under low-depth conditions.

bioinformatics↗

gAIRR-wgs: An Algorithm to Genotype T Cell Receptor Alleles Using Whole Genome Sequencing Data

T cell receptor (TR) genes, including variable (TR_V), diversity (TR_D), and joining (TR_J) segments, exhibit allelic diversity that is critical to adaptive immunity. Growing evidence has identified associations between TR genes and immune-related diseases. Germline variants may influence TR gene function and subsequent usage, highlighting the importance of accurate TR allele profiling. However, accurately identifying germline TR from standard WGS data remains challenging due to short read lengths, limited depth, and high sequence similarity. To address these challenges, we developed gAIRR-wgs, for WGS-based TR allele typing. By incorporating novel alleles from HPRC individuals, gAIRR-wgs exhibited excellent performance in allele calling, with F1 scores of 100.0% for TR_D, 99.8% for TR_J, and 98.3% for TR_V. Applying this pipeline to 1,492 individuals from the Taiwan Biobank (TWB), we identified 449 novel TR alleles, 277 of which overlapped with HPRC release 1 data of mixed ethnicity and are absent in the IMGT database. Further population comparison analysis revealed significant TR allele distribution differences across global populations, showing population-specific patterns and diversity variations between ethnic groups. We also discovered TWB-specific deletion polymorphisms affecting contiguous TRGV and TRBV genes, which are not recorded in the gnomAD database and undetected by standard structural variant callers, highlighting the need for tailored approaches to resolve complex immune gene regions. In conclusion, gAIRR-wgs enables accurate TR allele calling from standard WGS data using feasible computational resources and reveals substantial immunogenetic diversity in population cohorts.

bioinformatics↗

TypeAssembly: Copy number estimation and allele typing for haplotype assemblies

Accurately annotating complex genes in the human genome, particularly from haplotype assemblies, remains a significant challenge. To overcome this, we developed TypeAssembly, a local alignment-based framework for copy number estimation and allele typing. Operating in two modes, mode-FASTA and mode-VCF, TypeAssembly can define alleles by either sequence or variant information. We successfully applied it to annotate 41 genes in the MHC locus, 17 KIR genes, and, for the first time, 15 pharmacogenes across 466 haplotype assemblies. This study establishes TypeAssembly as a robust method for accurately annotating complex genomic regions and provides an evaluation of existing gene annotations and callers.

bioinformatics↗

Unmasking Human T Cell Receptor Germline Diversity: 335 Novel Alleles Identified in 47 Pangenome Reference Individuals Using the gAIRR Suite

The adaptive immune receptor repertoire (AIRR), composed of V(D)J-recombined T cell receptors (TR) and immunoglobulins (IG), is central to adaptive immunity. Accurate AIRR profiling depends on a comprehensive and diverse germline gene set encoding AIRR (gAIRR). Furthermore, gAIRR alleles themselves are associated with immune-related phenotypes and diseases. However, for TR genes, the IMGT database - the primary gAIRR reference - has not been updated since 2020 and lacks sufficient population diversity and complete flanking sequences. To address these limitations, we investigated 47 high-quality genomes from the Human Pangenome Reference Consortium (HPRC) using the gAIRR Suite and identified 335 novel TR alleles - 305 TRV and 30 TRJ - representing 91.6% and 30.9% increases over IMGT records. All novel alleles were crosschecked using two orthogonal pipelines. We also established a comprehensive flanking sequence database, including recombination signal sequences (RSS). We have made all resources publicly available to support immunogenomics research and clinical applications.

genomics↗

Graph-KIR: Graph-based KIR Copy Number Estimation and Allele Calling Using Short-read Sequencing Data

MotivationThe Killer-cell Immunoglobulin-like Receptor (KIR) is a highly polymorphic region in the human genome, associated with autoimmune diseases and organ transplantation. The sequences of KIR genes are highly similar among star alleles as well as in between individual genes, with the copy number of each KIR gene typically ranging from 0 to 4. In this study, we introduce a tool Graph-KIR that aims to estimate the copy number of genes and to call full-resolution (7-digit) KIR alleles from a whole genome sequencing (WGS) sample. ResultsGraph-KIR, unlike most KIR tools, is capable of independently typing KIR alleles per sample with no reliance on the distribution of any framework gene in a cohort. In a set of 100 simulated samples, Graph-KIR demonstrated 100% accuracy in copy number estimation and high accuracy of allele typing: 91.2% at 7-digit resolution, 97.0% at 5-digit resolution, 97.2% at 3-digit resolution, and 99.6% at gene-level resolution. Graph-KIR outperforms existing tools such as PINGs WGS version (91.9% accuracy) and T1K (84.6% accuracy) at 5-digit resolution. By analyzing the results on 44 HPRC samples, Graph-KIR achieves an accuracy of 85.0%, better than PINGs WGS version (75.5% accuracy) at 5-digit resolution. The release of Graph-KIR adds another valuable tool to assist users in accurately estimating copy numbers and calling alleles of KIR genes from WGS samples, ensuring reliable performance. AvailabilityThe Graph-KIR and paper-related pipeline codes are available at https://github.com/linnil1/KIR_graph.

bioinformatics↗

Genetic Diversity and Structural Complexity of the Killer-Cell Immunoglobulin-Like Receptor Gene Complex: A Comprehensive Analysis using Human Pangenome Assemblies

The killer-cell immunoglobulin-like receptor (KIR) gene complex, a highly polymorphic region of the human genome that encodes proteins involved in immune responses, poses strong challenges in genotyping due to its remarkable genetic diversity and structural intricacy. Accurate analysis of KIR alleles, including their structural variations, is crucial for understanding their roles in various immune responses. Leveraging the high-quality genome assemblies from the Human Pangenome Reference Consortium (HPRC), we present a novel bioinformatic tool, the Structural KIR annoTator (SKIRT), to investigate gene diversity and facilitate precise KIR allele analysis. We applied SKIRT on 47 HPRC-phased assemblies and identified a recurrent novel KIR2DS4/3DL1 fusion gene in the paternal haplotype of HG02630 and maternal haplotype of NA19240. Additionally, SKIRT accurately identifies eight structural variants and 17 novel nonsynonymous alleles, all of which were independently validated using short-read data or quantitative polymerase chain reaction. Our study has discovered a total of 570 novel alleles, among which eight haplotypes harbor at least one KIR gene duplication, six haplotypes have lost at least one framework gene, and 75 out of 94 haplotypes (79.8%) carry at least five novel alleles, thus confirming KIR genetic diversity. These findings are pivotal in providing insights into KIR gene diversity and serve as a solid foundation for understanding the functional consequences of KIR structural variations. High-resolution genome assemblies offer unprecedented opportunities to explore polymorphic regions that are challenging to investigate using short-read sequencing methods. The SKIRT pipeline emerges as a highly efficient tool, enabling the comprehensive detection of the complete spectrum of KIR alleles within human genome assemblies.

genomics↗

Reducing expression of dynamin-related protein 1 increases radiation sensitivity of glioblastoma cells

BackgroundDynamin-related protein 1 (DRP1) is a GTPase involved in mitochondrial fission, mitochondrial protein imports, and drug sensitivity, suggesting an association with cancer progression. This study is to evaluate the prognostic significance of DRP1 in glioblastoma multiforme (GBM).\n\nMaterial and MethodsDRP1 expression was measured by immunohistochemistry and Western blotting. Correlations between DRP1 expression and clinicopathological parameters were analyzed by statistical analysis. Differences in survival were compared by a log-rank test.\n\nResultsDRP1 expression was detected in 87.2% (41/47) patients with GBM. Patients with higher DRP1 levels had worse survival (p = 0.0398). In vitro, silencing of DRP1 reduced cell proliferation, metastatic potential, and radiation resistance. The addition of shikonin inhibited DRP1 expression and increased drug uptake. Moreover, shikonin reduced the nuclear entry of DNA repair-associated enzymes and increased radiation sensitivity, suggesting that to reduce DRP1 expression could inhibit DNA repair and increase the radiation sensitivity of GBM cells.\n\nConclusionOur results indicate that DRP1 overexpression is a prospective radio-resistant phenotype in GBM. Therefore, DRP1 could be a potential target for improving the effectiveness of radiation therapy.\n\nAbbreviations used are: ATAD3A, the ATPase family, AAA domain containing 3A; CIM, confocal immunofluorescence microscopy; DRP1, dynamin-related protein 1; ER, endoplasmic reticulum; GBM, glioblastoma multiforme; hHR23A, human homolog of yeast Rad23 protein A; IDH1, isocitrate dehydrogenase 1; MAM, mitochondria-associated membrane; MGMT, O6-methylguanine-DNA-methyltransferase; SAHA, suberoylanilide hydroxamic acid (vorinostat); TMZ, temozolomide\n\nTranslational RelevanceThis study shows that dynamin-related protein 1 (DRP1), an essential 80-kDa GTPase, which is involved in mitochondrial fission, and mitochondrial protein imports, is highly expressed in glioblastoma multiforme (GBM). Moreover, we demonstrate that DRP1 expression is closely associated with radiation sensitivity, cancer progression, and patients cumulative survival. In vitro, inhibition of DRP1 expression reduced the nuclear entry of DNA repair-associated enzymes, such as ATM, but increased radiation sensitivity and nuclear drug uptakes of glioblastoma cells. More importantly, the silencing of DRP1 induced cellular autophagy. These results indicate that DRP1 overexpression could be a prospective radio-resistant phenotype in GBM and a clinically important target for improving the effectiveness of radiation therapy.

cancer biology↗

TAO Kinase 3 Overexpression Is a Poor Prognosis Marker for Lung Adenocarcinoma and Predicts Paclitaxel Resistance

High expression of TAOK3 has been observed in several cancers, but very little about TAOK3-involved mechanisms has been reported. In this study, we investigated the role of TAOK3 in the therapeutic effect of paclitaxel treatment. Protein expression of TAOK3 was evaluated among 121 patients by using immunohistochemical staining. TAOK3 expression was estimated by analyzing the genes expression and its correlation with the IC50 of paclitaxel in cells. The expression of TAOK3 in lung cancer was highly correlated with poor overall survival, progression-free survival, and recurrence rate in lung cancer patients. The expression level of TAOK3 was positively correlated with paclitaxel resistance in the lung cancer cell lines. The depletion of TAOK3 could enhance the sensitivity of paclitaxel in lung cancer and vice versa. TAOK3 expression is associated with paclitaxel-resistance and could be a clinical predictor for disease recurrence and a potential therapeutic target in lung cancer.

cancer biology↗

Circular RNAs regulate cancer stem cells by FMRP against CCAR1 complex in hepatocellular carcinoma

Circular RNA (circRNA) possesses great pre-clinical diagnostic and therapeutic potentials in multiple cancers. However, the underlying correlation between circRNAs and cancer stem cells (CSCs) has not been reported. The absence of circZKSCAN1 endowed several malignant properties including cancer stemness and tightly correlated with worse overall and recurrence-free survival rate in HCC cells in vitro and in vivo. Bioinformatics analysis and RNA immunoprecipitation-sequencing (RIP-seq) results revealed that circZKSCAN1 exerted its inhibitive role by competitively binding FMRP, therefore, block the binding between FMRP and {beta}-catenin-binding protein-cell cycle and apoptosis regulator 1 (CCAR1) mRNA, and subsequently restraining the transcriptional activity of Wnt signaling. In addition, RNA-splicing protein Quaking 5 was found downregulated in HCC tissues and responsible for the reduction of circZKSCAN1. Collectively, this study revealed the mechanisms underlying the regulatory role of circZKSCAN1 in HCC CSCs and identified the newly discovered Qki5- circZKSCAN1-FMRP-CCAR1-Wnt signaling axis as a potentially important therapeutic target for HCC treatment.\n\nStatement of significanceO_LICircZKSCAN1, a novel negative regulator for cancer stem cells, was firstly identified with reverse correlation with HCC prognosis.\nC_LIO_LICircZKSCAN1 directly targets FMRP, and competitive binding with {beta}-catenin-binding protein cell cycle and apoptosis regulator 1 (CCAR1) for its activity.\nC_LIO_LIThe decreased expression of Quaking 5 is responsible for the absence of circZKSCAN1 in HCC.\nC_LI

cancer biology↗

Naa10p promotes metastasis by stabilizing matrix metalloproteinase-2 protein in human osteosarcomas

N--Acetyltransferase 10 protein (Naa10p) mediates N-terminal acetylation of nascent proteins. Oncogenic or tumor suppressive roles of Naa10p were reported in cancers. Here, we report an oncogenic role of Naa10p in promoting metastasis of osteosarcomas. Higher NAA10 transcripts were observed in metastatic osteosarcoma tissues compared to non-metastatic tissues and were also correlated with a worse prognosis of patients. Knockdown and overexpression of Naa10p in osteosarcoma cells respectively led to decreased and increased cell migratory/invasive abilities. Re-expression of Naa10p, but not an enzymatically inactive mutant, relieved suppression of the invasive ability in vitro and metastasis in vivo imposed by Naa10p-knockdown. According to protease array screening, we identified that matrix metalloproteinase (MMP)-2 was responsible for the Naa10p-induced invasive phenotype. Naa10p was directly associated with MMP-2 protein through its acetyltransferase domain and maintained MMP-2 protein stability via NatA complex activity. MMP-2 expression levels were also significantly correlated with Naa10p levels in osteosarcoma tissues. These results reveal a novel function of Naa10p in the regulation of cell invasiveness by preventing MMP-2 protein degradation that is crucial during osteosarcoma metastasis.

cancer biology↗