Biology subjects

Wang, Y.-B.

Publications and source records attributed to Wang, Y.-B..

5 recordsLinked to original sources

bioRxiv2026

Ancestral Musaceae karyotype reconstruction provides insights into chromosome evolution and bract coloration

The banana family (Musaceae) exhibits remarkable diversity in both karyotype structure and bract coloration, yet the evolutionary dynamics of chromosomes and the genomic and regulatory basis underlying color diversification remain poorly understood. Here, we present a telomere-to-telomere (T2T), gap-free genome assembly of Musa exotica, an ornamental species with brightly colored bracts occupying an early-branching lineage within sect. Callimusa (Musa L.). By integrating this high-quality genome with other available Musaceae genomes, we reconstruct the ancestral Musaceae karyotype (AMK) for the first time, inferring a haploid chromosome number of n = 17. Comparative genomic analyses reveal recurrent, highly complex lineage-specific inter-chromosome rearrangements across extant Musaceae lineages, leading to inferred stepwise reductions in chromosome number to n = 11, 10, and 9. Notably, closely related species share similar rearrangement patterns, suggesting conserved evolutionary trajectories shaped by lineage-specific structural remodeling. Strikingly, rearrangement-associated regions are enriched for functionally important genes, particularly structural genes (CHS and F3H) and regulatory transcription factors (MYB and bHLH) involved in the anthocyanin biosynthesis pathway. Integrative transcriptomic and regulatory analyses further demonstrate coordinated activation of anthocyanin biosynthetic genes (CHS, CHI, F3'5'H, and ANS) in bracts, with expression divergence largely decoupled from gene dosage and predominantly driven by transcriptional regulation. Co-expression analyses reveal extensive MYB- and bHLH-enzyme interactions, underscoring their central role in modulating pathway activity and bract coloration diversity. Collectively, our findings suggest a link between genome structural evolution to trait diversification, offering a refined framework for understanding genome evolution and phenotypic diversification in Musaceae and other monocots. SignificanceWe reconstructed the ancestral Musaceae karyotype and revealed extensive lineage-specific chromosome rearrangements underlying karyotype evolution. Rearrangement-associated regions are enriched for anthocyanin biosynthetic and regulatory genes, suggesting that genome structural evolution may have contributed to bract coloration diversification in Musaceae. Integrative transcriptomic analyses further indicate that variation in anthocyanin-mediated bract coloration is more closely associated with transcriptional regulation than with gene dosage alone.

evolutionary biology↗

bioRxiv2025

The Sequential Multispecies Coalescent

The multispecies coalescent (MSC) model applies coalescent theory to gene evolution within and among reproductively isolated populations ("species") to estimate a species tree in the face of gene tree conflict resulting from deep coalescence. Sequential Monte Carlo (SMC) uses particle filtering to sample a posterior distribution, providing a fully-Bayesian and easily parallelized alternative to traditional MSC tree inference approaches. The method we propose samples first from the joint posterior distribution of gene and species trees, then samples species trees conditional on gene trees sampled previously, employing SMC for both rounds. Analyses of simulated and empirical datasets yield results comparable to state-of-the-art Bayesian MCMC approaches. Sampling the multispecies coalescent using SMC retains the advantages of fully Bayesian methods and is parallelizable in ways that Bayesian MCMC methods are not but also adds unique challenges. We demonstrate the performance of SMC compared to other commonly-used species tree methods using two empirical datasets and 400 simulated datasets.

evolutionary biology↗

bioRxiv2024

Toward Automatic Variant Interpretation: Discordant Genetic Interpretation Across Variant Annotations for ClinVar Pathogenic Variants

PurposeHigh-throughput sequencing has revolutionized genetic disorder diagnosis, but variant pathogenicity interpretation is still challenging. Even though the Human Genome Variation Society (HGVS) provides recommendations for variant nomenclature, discrepancies in annotation remain a significant hurdle. MethodsThis study evaluated the annotation concordance between three tools-- ANNOVAR, SnpEff, and Variant Effect Predictor (VEP)--using 164,549 two-star variants from ClinVar. The analysis used HGVS nomenclature string-match comparisons to assess annotation consistency from each tool, corresponding coding impacts, and associated ACMG criteria inferred from the annotations. ResultsThe analysis revealed variable concordance rates, with 58.52% agreement for HGVSc, 84.04% for HGVSp, and 85.58% for the coding impact. SnpEff showed the highest match for HGVSc (0.988), while VEP bettered for HGVSp (0.977). The substantial discrepancies were noted in the Loss-of-Function (LoF) category. Incorrect PVS1 interpretations affected the final pathogenicity and downgraded PLP variants (ANNOVAR 55.9%, SnpEff 66.5%, VEP 67.3%), risking false negatives of clinically relevant variants in reports. ConclusionsThese findings highlight the critical challenges in accurately interpreting variant pathogenicity due to discrepancies in annotations. To enhance the reliability of genetic variant interpretation in clinical practice, standardizing transcript sets and systematically cross-validating results across multiple annotation tools is essential. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/617756v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@9f6378org.highwire.dtl.DTLVardef@3b9a2corg.highwire.dtl.DTLVardef@106fb58org.highwire.dtl.DTLVardef@15f70c8_HPS_FORMAT_FIGEXP M_FIG This study examined the consistency of variant annotations produced by three widely used open-source toolsANNOVAR, SnpEff, and VEPagainst 164,549 ClinVar two starts variants. The investigation covers HGVS-based transcript, protein nomenclature and coding impact annotation. The results showed that none of the tools were fully consistent with ClinVar across all coding impact categories, particularly in the LoF category, which exhibited the poorest consistency. This inconsistency may lead to discrepancies in PVS1 interpretation, affecting the final pathogenicity assessment. PVS1 loss resulted in a significant downgrading of PLP variants, potentially leading to the omission of clinically relevant variants in reports. C_FIG

genomics↗

bioRxiv2023

Somatic mutation detection workflow validity distinctly influences clinical decision.

Evaluating robustness of somatic mutation detections is essential when utilizing whole exome sequencing (WES) for treatment decision-making. A comprehensive evaluation was conducted using tumor WES from the FDA-led Sequencing Quality Control Phase 2 (SEQC2) project, in which multiple library kits sequenced identical DNA materials across three labs to benchmark analytical validity. These workflows included various read aligner (BWA, Bowtie2, DRAGEN-Aligner, DRAGMAP, and HISAT2) and mutation caller (Mutect2, TNscope, DRAGEN-Caller, and DeepVariant) combinations. The results revealed that DRAGEN exhibited superior performance, achieving mean F1-scores of 0.966 and 0.791 for SNV and INDEL detection, respectively. Among open-source software, BWA Mutect2 and HISAT2 Mutect2 combinations showed the highest mean F1-scores for SNV (0.949) and IN-DEL (0.722), respectively. The analyses indicated that high-quality data can be analyzed as having worse results, and vice versa. Evaluations of COSMIC reported mutations unveiled discrepancies across enrichment kits. IDT enrichment kits showed a higher false negative rate, while Agilent WES kits tended to miss mutations in CBL and IDH1, and Roche library kits tended to miss the mutations in PIK3CB. For drug-related biomarkers, Sentieon TNscope tended to underestimate tumor mutation burden and overlook crucial drug-resistance mutations such as FLT3 (c.G1879A: p.A627T) for cytarabine resistance in leukemia and MAP2K1 (c.G199A:p.D67N) for BRAF inhibitors in melanoma. The findings highlight the importance of robust bioinformatic analysis in identifying tumor mutations and guiding clinical decision-making. HighlightsO_LIMutation callers had a significantly higher effect on overall sensitivity than aligners. C_LIO_LIBenchmarking analyses demonstrated that high-quality sequencing reads can be analyzed as having worse results, and vice versa. C_LIO_LIDRAGEN exhibited the best performance among other aligner-caller combinations. C_LIO_LIThe combination of BWA with Mutect2 and HISAT2 with Mutect2 yielded the highest mean F1 scores for detecting SNVs and INDELs by open-source software, respectively. C_LIO_LISentieon TNscope tended to underestimate the tumor mutation burden and missed several drug-resistant mutations. C_LI

bioinformatics↗

bioRxiv2022

New efficient intercellular spread mode of respiratory syncytial virus contributes to neutralization escape and persistence

There is no licensed vaccine or therapeutic antibody for respiratory syncytial virus (RSV). The induction of high-titer, potent neutralizing antibodies cannot completely inhibit breakthrough infection and enhanced respiratory disease (ERD), encouraging a focus on the relationship between virus intercellular spread and neutralizing antibodies. By blocking the known intercellular spread modes and with the aid of ultrahigh-resolution imaging, we observed a new efficient mode of intercellular spread in which RSV-infected cells directly transfer viral materials (including viral replication factories) to neighboring cells through protruding open-ended microfilament-rich intercellular nanotubes. The new mode is virion-independent and antibody-insensitive, beginning as early as 3 h post infection. Furthermore, replication-defective viral genomes (DVGs) might also utilize the new mode, facilitating the establishment of latent viral infections. Therefore, our data provide a new perspective on RSV cell-to-cell spread and might help to explain the immune escape and latent persistence of paramyxoviruses.

microbiology↗