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Biology subjects

Yen, M.-R.

Publications and source records attributed to Yen, M.-R..

6 recordsLinked to original sources

BryoCAD: Extending Plant DNA Foundation Models Beyond Flowering Plants

Bryophytes exhibit diverse genome architectures and gene repertoires, yet their functional interpretation remains constrained by incomplete genomic annotations and limited experimental resources. Although DNA foundation models offer promising solutions, their applicability to evolutionarily divergent bryophytes remains largely unexplored. Here, we introduce BryoCAD, a DNA language model developed through continued pre-training of the angiosperm-specific PlantCAD2 model on 17 bryophyte genomes spanning hornworts, liverworts, and mosses. Across three representative bryophyte genomes and four gene-boundary motif recovery tasks, BryoCAD-Small improved mean zero-shot accuracy from 45.7% to 57.0%, a 24.8% relative increase over PlantCAD2-Small, while the over 200-fold larger Evo2-20B achieved a mean accuracy of only 39.3%. Remarkably, BryoCAD-Small outperformed PlantCAD2-Large in 11 of 12 motif-recovery comparisons across the three bryophytes, highlighting the benefits of lineage-specific adaptation over model scaling alone. These improvements extended to all six tested algal species, increasing mean accuracy from 26.3% to 37.5%, although performance varied across ferns and gymnosperms. BryoCAD also enhanced gene structure annotation: replacing PlantCAD2-Small with BryoCAD-Small increased transcript-level F1 scores from 0.578 to 0.625 in Marchantia polymorpha and from 0.485 to 0.530 in Physcomitrium patens. Together, our findings demonstrate that lineage-specific continued pre-training enhances genomic sequence interpretation and gene annotation across bryophytes, providing a transferable framework for extending DNA foundation models to evolutionarily diverse, understudied plant lineages.

evolutionary biology↗

TISCalling: Leveraging Machine Learning to Identify Translational Initiation Sites in Plants and Viruses

The recognition of translational initiation sites (TISs) offers complementary insights into identifying genes encoding novel proteins or small peptides. Conventional computational methods primarily identify Ribo-seq-supported TISs and lack the capacity of systematical and global identification of TIS, especially for non-AUG sites in plants. Additionally, these methods are often unsuitable for evaluating the importance of mRNA sequence features for TIS determination. In this study, we present TISCalling, a robust framework that combines machine learning (ML) models and statistical analysis to identify and rank novel TISs across eukaryotes. TISCalling generalized and ranks important features common to multiple plant and mammalian species while identifying kingdom-specific features such as mRNA secondary structures and G-contents. Furthermore, TISCalling achieved high predictive power for identifying novel viral TISs. Importantly, TISCalling provides prediction scores for putative TIS along plant transcripts, enabling prioritization of those of interest for further validation. We offer TISCalling as a command-line-based package [https://github.com/yenmr/TIScalling], capable of generating prediction models and identifying key sequence features. Additionally, we provide web tools [https://predict.southerngenomics.org/TIScalling] for visualizing pre-computed potential TISs, making it accessible to users without programming experience. The TISCalling framework offers a sequence-aware and interpretable approach for decoding genome sequences and exploring functional proteins in plants and viruses.

bioinformatics↗

Evolutionarily Conserved Heat-Induced Chromatin Dynamics Drive Heat Stress Responses in Plants

Eukaryotic organisms remodel chromatin landscapes to regulate gene expression in response to environmental stress. In plants, heat stress (HS) induces widespread chromatin changes, yet the role of heat-responsive Heat Shock Transcription Factors (HSFs) in chromatin remodeling and their evolutionary conservation remains unclear. Using chromatin accessibility profiling and transcriptomics in Marchantia polymorpha hsf mutants, we identify HSFA1 as a key determinant in positioning cis-regulatory elements (CREs) for HS-induced gene activation, a mechanism conserved across land plants, mice, and human cells. By integrating gene regulatory network modeling, we identify parallel transcription factor subnetworks, with MpWRKY10 and MpABI5B acting as indirect regulators of HS responses via phenylpropanoid pathways and general stress signaling. We further explore crosstalk between HS and abscisic acid (ABA) signaling, showing that while ABA modulates gene expression in an HSFA1-dependent manner, it does not induce broad chromatin remodeling, positioning it as a downstream regulator rather than a primary determinant of chromatin dynamics. To extend these insights, we develop a cross-species and cross-condition machine learning framework that accurately predicts chromatin accessibility and gene expression, demonstrating a conserved regulatory logic of stress-responsive chromatin and transcription dynamics. Our findings provide a conceptual framework for understanding how TFs coordinate chromatin architecture to drive stress adaptation in plants and potentially other eukaryotes.

plant biology↗

RGF1 controls PLT2 protein stability through ROS-dependent regulation of a cysteine residue in root meristem development

The protein concentration gradients of the master regulators of the root meristem, named the PLETHORA proteins, modulate the root meristem size. Root meristem growth factor 1 (RGF1) peptide extends the PLETHORA2 (PLT2) protein gradients by altering reactive oxygen species (ROS) distributions. However, the underlying mechanism through which the ROS alterations regulate PLT2 remains unknown. Here, we demonstrate that the 212th cysteine of the PLT2 protein plays a pivotal role in modulating PLT2 stability through the ROS altered by RGF1. The substitution of the 212th cysteine of PLT2 with serine (PLT2C212S) enhanced the PLT2 protein stability upon RGF1 and resulted in robust resistance to ROS relative to the native PLT2. Accordingly, PLT2C212S modulated expressions of certain specific root development-related genes to a greater extent than native PLT2. In summary, these findings show that the PLT2 concentration gradient formation through ROS, modulated by RGF1, is dependent on a mechanism involving the 212th cysteine of PLT2.

plant biology↗

BSImp: imputing partially observed methylation patterns for evaluating methylation heterogeneity

DNA methylation is one of the most studied epigenetic modifications that has applications ranging from transcriptional regulation to aging, and can be assessed by bisulfite sequencing (BS-seq) at single base-pair resolution. The permutations of methylation statuses at bisulfite converted reads reflect the methylation patterns of individual cells. These patterns at specific genomic locations are sought to be indicative of cellular heterogeneity within a cellular population, which are predictive of developments and diseases; therefore, methylation heterogeneity has potentials in early detection of these changes. Computational methods have been developed to assess methylation heterogeneity using methylation patterns formed by four CpGs, but the nature of shotgun sequencing often give partially observed patterns, which makes very limited data available for downstream analysis. While many programs are developed to impute methylation levels genomewide, currently there is only one method developed for recovering partially observed methylation patterns; however, the program needs lots of data to train and cannot be used directly; therefore, we developed a probabilistic-based imputation method that uses information from neighbouring sites to recover partially observed methylation patterns speedily. It is demonstrated to allow for the evaluation of methylation heterogeneity at three times more regions genome-wide with high accuracy for data with moderate depth. To make it more user-friendly we also provide a computational pipeline for genome-screening, which can be used in both evaluating methylation levels and profiling methylation patterns genomewide for all cytosine contexts, which is the first of its kind. Our method allows for accurate estimation of methylation levels and makes evaluating methylation heterogeneity available for much more data with reasonable coverage, which has important implications in using methylation heterogeneity for monitoring changes within the cellular populations that were impossible to detect for the assessment of development and diseases.

bioinformatics↗

The histone deacetylase HDA15 interacts with MAC3A and MAC3B to regulate intron retention of ABA-responsive genes

Histone deacetylases (HDAs) play an important role in transcriptional regulation involved in multiple biological processes. In this study, we investigate the function of HDA15 in abscisic acid (ABA) responses. Immunopurification coupled with mass spectrometry-based proteomics was used to identify the HDA15 interacting proteins. We found that HDA15 can interact with the core subunits of MOS4-Associated Complex (MAC), MAC3A and MAC3B. In addition, ABA enhances the interaction of HDA15 with MAC3B. hda15 and mac3a/mac3b mutants are ABA-insensitive in seed germination and hyposensitive to salinity. RNA sequencing (RNA-seq) analysis demonstrate that HDA15 and MAC3A/MAC3B not only affect the expression of ABA-related genes, but also regulate ABA-responsive intron retention (IR). Furthermore, HDA15 and MAC3A/MAC3B reduce the histone acetylation level of the genomic regions near ABA-responsive IRs. Our studies uncovered the role of histone deacetylation in ABA-mediated splicing regulation and identified that HDA15-MAC3A/MAC3B acts as an important regulation module to mediate splicing of introns in ABA responses. One Sentence SummaryHDA15 and MAC3A/MAC3B coregulate intron retention and reduce the histone acetylation level of the genomic regions near ABA-responsive retained introns.

plant biology↗