Biology subjects

Yeh, Y.-C.

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

14 recordsLinked to original sources

bioRxiv2026

High culturable diversity and climate-associated seasonal dynamics of Saccharomycotina yeasts in subtropical forest leaf litter

Forest-associated Saccharomycotina occur at low relative abundance, limiting inference about their diversity and dynamics. We sampled leaf litter weekly for 47 weeks across a subtropical forest in northern Taiwan. Enrichment, isolation and ITS sequencing recovered 687 isolates, including 613 Saccharomycotina representing 56 described species and 77 putatively novel operational taxonomic units. Rarefaction indicated unsampled culturable diversity. Among litter traps, community dissimilarity was high and dominated by taxon replacement, but neither topography nor geographic distance was associated with composition, and turnover matched randomised expectations. Richness peaked during warm, wet periods and declined in winter, and minimum temperature showed the strongest statistical association. Composition was associated with maximum temperature, minimum relative humidity, precipitation and solar radiation. Selected isolates' thermal optima covaried with collection-week temperatures, and two October Magnusiomyces magnusii isolates had higher optima than four winter isolates. Together, these findings reveal substantial culturable diversity and seasonal community restructuring consistent with temperature-related filtering.

microbiology↗

bioRxiv2026

Histopathology-inferred spatial transcriptomics characterizes the tumor microenvironment in 1,500 head and neck tumors and predicts clinical outcomes

Head and neck squamous cell carcinoma (HNSC) is a prevalent malignancy associated with poor prognosis despite recent therapeutic advances. We hypothesized that a comprehensive understanding of the spatial heterogeneity and organization of the tumor microenvironment (TME) can substantially improve risk stratification and prediction of treatment response in HNSC. As spatial transcriptomics (ST) remains labor-intensive and costly, we developed HEiST (H&E-Inferred Spatial Transcriptomics), a deep learning framework that predicts spatially resolved gene expression profiles directly from routine hematoxylin and eosin (H&E)-stained histology slides. After rigorous validation across two independent external ST cohorts, we applied HEiST to infer spatial transcriptomes across 1,500 HNSC patient tumors spanning two publicly available datasets and two newly generated cohorts, one treated with concurrent chemoradiotherapy (CCRT) and one with immunotherapy. This large-scale analysis uncovered reproducible spatial clusters characterizing the HNSC TME, defining two distinct prognostic Spatiotypes, Immune-Exhausted and Immune-Activated, with significantly distinct survival outcomes. Critically, spatial cluster composition accurately predicts HPV status and yields treatment response predictors for both CCRT/radiotherapy and immunotherapy that outperform costly gene-expression and direct image-based approaches. Notably, the ST cluster-based predictor of immunotherapy response markedly surpasses the performance of commonly used FDA-approved biomarkers, including CPS, TPS, and their combination. To the best of our knowledge, this represents the first virtual spatial profiling effort and the most comprehensive large-scale spatial TME analysis in HNSC to date. HEiST thus introduces a scalable, low-cost, and spatially grounded biomarker discovery for precision oncology in HNSC.

cancer biology↗

bioRxiv2026

A haploid wild yeast resource for exploring the natural ecology of Saccharomyces cerevisiae

Saccharomyces cerevisiae predominantly exists as diploid cells in nature, a life-cycle feature that limits classical genetic analyses of wild populations. Here, we establish a stable haploid strain collection derived from 33 diverse Taiwanese S. cerevisiae isolates through targeted disruption of the HO endonuclease gene. This resource spans predomesticated Asian wild lineages and enables systematic analyses of mating compatibility, reproductive isolation, and ecological trait variation. Although all pairwise hybridizations formed zygotes, many produced low spore viabilities, revealing strong postzygotic barriers. Genome analyses show that reduced hybrid fertility is primarily associated with chromosomal inversions and inter-chromosomal rearrangements rather than sequence divergence, indicating that structural variation maintains lineage separation despite geographic coexistence. Phenotypic profiling uncovered marked ecological differentiation, with the most diverged TW1 lineage favoring cooler growth conditions and a naturally occurring hybrid exhibiting heterosis with expanded thermal tolerance. While most wild strains grew poorly on maltose, two anthropogenically associated strains displayed enhanced maltose utilization linked to functional MAL regulatory alleles and maltose-specific transporters. Together, these findings demonstrate how structural genomic variation and metabolic gene divergence drive ecological and reproductive divergence in wild S. cerevisiae and establish this haploid collection as a platform for studying yeast evolution in nature.

genetics↗

bioRxiv2025

Eco-genomic analysis uncovers precision-conservation targets for the western Pacific's southernmost salmonid

Understanding how isolated small populations persist and adapt in adverse environments is instrumental to evolutionary and conservation biology. We combine a chromosome-level genome assembly, population resequencing and forward-time simulations to reconstruct the history and viability of the Formosan landlocked salmon (Oncorhynchus formosanus), now restricted to a handful of high-mountain headwaters in Taiwan. We estimate that this lineage has diverged from Japanese masu salmon over one million years ago and has no detectable gene flow for [~]50,000 years. It has accumulated extensive chromosome fusions and expansions of cold-adaptation gene families, qualifying it as a new species rather than a subspecies of Japanese masu salmon. Whole-stream sampling reveals an overlooked Hehuan-Creek population that retains high heterozygosity and has gained unique alleles. Life-table simulations show that the Hehuan population has a notably lower extinction risk and can persist or even grow under low-to-moderate typhoon frequency, whereas Qijiawan-Creek population would decline precipitously under the same or higher frequency . These findings contradict the notion that peripheral populations are likely genetically depleted and support stream-specific "precision conservation" in place of broad, untargeted translocations that could erode local adaptation potential. Thus, our genomic-ecological analysis has uncovered hidden strong resilience in a critically endangered, climate-threatened salmonid lineage.

genomics↗

bioRxiv2025

The JEDI marker as a universal measure of planetary biodiversity

Despite its critical importance in the formation and maintenance of ecosystems and homeostasis on Earth, biodiversity remains a complex and non-unified concept. Consequently, standards for measuring global biodiversity are lacking, hindering our capacity to document Earths biota and track its change. Here, we propose the Joint, cellular life-Encompassing DIversity (JEDI) marker as a simple, effective and quantitative measure to assess and monitor biodiversity. The JEDI marker is a ribosomal RNA gene fragment that can be amplified from all domains of life using a single pair of PCR primers. We demonstrate the applicability and effectiveness of this approach for assessing biodiversity across ecological and biological scales, from holobionts to diverse ecosystems. In addition, we provide an automated bioinformatic workflow to support the standardised and reproducible analysis of the JEDI marker in future studies. While this approach is not free from trade-offs, we argue that its advantages outweigh its limitations by providing a unique, operational and scalable solution that builds on established infrastructure to integrate the microbial majority into biodiversity assessments and provide fundamental insights into organismal dynamics and associations across domains of life. Thus, the JEDI marker approach addresses the urgent need for a universal and standardised framework to effectively measure and monitor biodiversity at planetary scales in an era of profound global change.

ecology↗

bioRxiv2024

The Taiwan Precision Medicine Initiative: A Cohort for Large-Scale Studies

The Taiwan Precision Medicine Initiative (TPMI), a project initiated by the Academia Sinica in collaboration with 16 major medical centers around Taiwan, has recruited 565,390 participants who consented to provide DNA samples for genetic profiling and grant access to their electronic medical records (EMR) for studies to develop precision medicine. Access to the EMR is both retrospective and prospective, allowing researchers to conduct prospective studies over time. Genetic profiling is done with population-optimized SNP arrays for the Han Chinese populations that enable genetic analyses such as genome-wide association, phenome-wide association, and polygenic risk score studies to evaluate common disease risk and pharmacogenetic response. Furthermore, the TPMI participants agree to be contacted for future research opportunities related to their genetic risks and receive personalized genetic risk profiles with health management recommendations. TPMI has established the TPMI Data Access Platform (TDAP), a central database and analysis platform that both safeguards the security of the data and facilitates academic research. The TPMI is the largest non-European cohort that merges genetic profiles with EMR in the world. With a cohort that can be followed over time, it can be utilized to validate genetic risk prediction models, conduct clinical trials to show the efficacy of risk-based health management, and optimize health policies based on genetic risks. In this report, we describe the TPMI study design, the population and genetic characteristics of the TPMI cohort, and the power it provides to conduct crucial studies in developing precision medicine on a population and personal level. As Han Chinese represent almost 20% of the worlds population, the results of TPMI studies will benefit >1.4 billion people around the world and serve as a model for developing population-based precision medicine.

genetics↗

bioRxiv2024

Enhanced Pooling for Weakly Supervised Gigapixel WSI Training Improves Classification and Lesion Localization

A robust artificial intelligence-assisted workflow for tumor assessment in pathology requires not only accurate classification but also precise lesion localization. While current weakly supervised learning methods significantly reduce the need for extensive annotations and leverage large quantities of annotation-free whole-slide images (WSIs) to enhance classification robustness, they often fall short in segmentation accuracy. We attribute this limitation to the optimization goals in classification, which tend to focus solely on the most representative features--an approach that is particularly inefficient for WSIs with gigapixel resolution. To address this challenge, we introduce a novel approach based on streaming convolution, an end-to-end method for WSI training. Our contributions include the Rectified LogSumExp (ReLSE) pooling method and adaptive pseudo annotation generation for self-training, both designed to encourage models to learn from sub-representative features. Using only slide-level annotations from the CAMELYON16 dataset, our method achieves a significant improvement in metastasis localization, with a patch-level recall from 53.88% to 79.18% at a precision of 80%. This conclusion also holds for a dataset collected from Taipei Veterans General Hospital (TVGH), used in the assessment of lung cancer lymph node metastasis with a recall improved from 42.98% to 72.27%. The proposed method can also be integrated with additional manual annotations. Experiment results showed the semi-supervised model (recall: 91.12%) could even outperform the strongly supervised model (recall: 81.80%) on the TVGH dataset.

bioinformatics↗

bioRxiv2024

Phylogenetic proximity drives temporal succession of marine giant viruses in a five-year metagenomic time-series

Nucleocytoplasmic Large DNA Viruses (NCLDVs, also called giant viruses) are widespread in marine systems and infect a broad range of microbial eukaryotes (protists). Recent biogeographic work has provided global snapshots of NCLDV diversity and community composition across the worlds oceans, yet little information exists about the guiding rules underpinning their community dynamics over time. We leveraged a five-year monthly metagenomic time-series to quantify the community composition of NCLDVs off the coast of Southern California and characterize these populations temporal dynamics. NCLDVs were dominated by Algavirales (Phycodnaviruses, 59%) and Imitervirales (Mimiviruses, 36%). We identified clusters of NCLDVs with distinct classes of seasonal and non-seasonal temporal dynamics. Overall, NCLDV population abundances were often highly dynamic with a strong seasonal signal. The Imitervirales group had highest relative abundance in the more oligotrophic late summer and fall, while Algavirales did so in winter. Generally, closely related strains had similar temporal dynamics, suggesting that evolutionary history is a key driver of the temporal niche of marine NCLDVs. However, a few closely-related strains had drastically different seasonal dynamics, suggesting that while phylogenetic proximity often indicates ecological similarity, occasionally phenology can shift rapidly, possibly due to host-switching. Finally, we identified distinct functional content and possible host interactions of two major NCLDV orders-including connections of Imitervirales with primary producers like the diatom Chaetoceros and widespread marine grazers like Paraphysomonas and Spirotrichea ciliates. Together, our results reveal key insights on season-specific effect of phylogenetically distinct giant virus communities on marine protist metabolism, biogeochemical fluxes and carbon cycling.

ecology↗

bioRxiv2022

Symbiotic diazotrophic UCYN-A strains co-occurred with El Ni&ntildeo, relaxed upwelling, and varied eukaryotes over 10 years off Southern California Bight

Biological nitrogen fixation, the conversion of N2 gas into a more bioavailable form, is vital to sustaining marine primary production. Studies have shifted beyond traditionally studied tropical diazotrophs. Candidatus Atelocyanobacterium thalassa (or UCYN-A) has emerged as a research focal point due to its streamlined metabolism, intimate partnership with a haptophyte host, and broad distribution. Here, we explore the abiotic factors that govern UCYN-As presence at the San Pedro Ocean Time-series (SPOT), its partner fidelity, and statistical interactions with non-symbiotic eukaryotes. 16S and 18S rRNA sequences were amplified by "universal primers" from monthly samples and resolved into Amplicon Sequence Variants, allowing us to observe multiple UCYN-A symbioses. UCYN-A1 relative abundances increased following the 2015-2016 El Nino event. When this "open ocean ecotype" was present, coastal upwelling ceased, and Ekman transport brought tropical waters into the region. Network analyses reveal all strains of UCYN-A co-occur with dinoflagellates including Lepidodinium, a potential predator, and parasitic Syndiniales. UCYN-A2 appeared to pair with multiple hosts and was not tightly coupled to its predominate host, while UCYN-A1 maintained a strong host-symbiont relationship. These biological relationships are particularly important to study in the context of climate change, which will alter UCYN-A distribution patterns both locally and globally.

microbiology↗

bioRxiv2021

Trade-off between competition ability and invulnerability to predation in marine microbes; protist grazing versus viral lysis effects

Trade-offs between competition ability and invulnerability to predation are important mechanisms explaining how predation promotes bacterial diversity. However, existence of these trade-offs has apparently not been investigated in natural marine bacterial communities. Here, we address this question with growth-based measurements for each marine bacterial taxon by conducting on-board dilution experiments to manipulate predation pressure and using high-throughput sequencing to assess the response of bacterial communities. We determined that bacterial taxa with a higher predation-free growth rate were accompanied with higher predation-caused mortality, supporting existence of competitiveness-invulnerability trade-off. This trade-off was stronger and more consistent under viral lysis than protist grazing. In addition, predation generally flattened out the rank-abundance distribution and increased the evenness and richness of the bacterial community. These findings supported the "Kill-the-Winner" hypothesis. All experiments supported a significant competitiveness-invulnerability trade-off, but there was substantial variation among bacterial communities in response to predation across experiments conducted in various sites and seasons. Therefore, we inferred that the Kill-the-Winner hypothesis is important but likely not the only deterministic mechanism explaining how predation shapes bacterial assemblages in natural marine systems.

ecology↗

bioRxiv2020

Ribosome-linked mRNA-rRNA chimeras reveal active novel virus-host associations.

Viruses of prokaryotes greatly outnumber their hosts1 and impact microbial processes across scales, including community assembly, evolution, and metabolism1. Metagenomic discovery of novel viruses has greatly expanded viral sequence databases, but only rarely can viral sequences be linked to specific hosts. Here, we adapt proximity ligation methods to ligate ribosomal RNA to transcripts, including viral ones, during translation. We sequenced the resulting chimeras, directly linking marine viral gene expression to specific hosts by transcript association with rRNA sequences. With a sample from the San Pedro Ocean Time-series (SPOT), we found viral-host links to Cyanobacteria, SAR11, SAR116, SAR86, OM75, and Rhodobacteracae hosts, some being the first viruses reported for these groups. We used the SPOT viral and cellular DNA database to track abundances of multiple virus-host pairs monthly over 5 years, e.g. with Roseovarius phages tracking the host. Because the vast majority of proximity ligations should occur between an organisms ribosomes and its own transcripts, we validated our method by looking for self- vs non-self mRNA-rRNA chimeras, by read recruitment to marine single amplified genomes; verifiable non-self chimeras, suggesting off-target linkages, were very rare, indicating host-virus hits were very unlikely to occur by mistake. This approach in practice could link any transcript and its associated processes to specific microorganisms.

microbiology↗

bioRxiv2020

Conformational surveillance of Orai1 by a rhomboid intramembrane protease prevents inappropriate CRAC channel activation

Calcium influx through plasma membrane calcium release-activated calcium (CRAC) channels, which are formed of hexamers of Orai1, is a potent trigger for many important biological processes, most notably in T cell mediated immunity. Through a bioinformatics-led cell biological screen, we have identified Orai1 as a substrate for the rhomboid intramembrane protease, RHBDL2. We show that RHBDL2 prevents stochastic signalling in unstimulated cells through conformational surveillance and cleavage of inappropriately activated Orai1. A conserved, disease-linked proline residue is responsible for RHBDL2 recognising only the active conformation of Orai1, and cleavage by RHBDL2 is required to sharpen switch-like signalling triggered by store-operated calcium entry. Loss of RHBDL2 control of Orai1 causes severe dysregulation of CRAC channel effectors including transcription factor activation, inflammatory cytokine expression and T cell activation. We propose that this seek-and-destroy function may represent an ancient activity of rhomboid proteases in degrading unwanted signalling proteins.

biochemistry↗

bioRxiv2019

Comprehensive single-PCR 16S and 18S rRNA community analysis validated with mock communities and denoising algorithms

Universal SSU rRNA primers allow comprehensive quantitative profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show all rRNA gene relative gene abundances, they are rarely used due to concerns about length bias against 18S amplicons and bioinformatic challenges converting mixed 16S/18S sequences into amplicon sequence variants. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this three-domain approach. To test for length biases, we mixed eukaryotic and prokaryotic mocks before PCR, and found consistent two-fold underestimation of longer 18S sequences due to sequencing but not PCR bias. Using these mocks, we show universal V4-V5 primers (515Y/926R) outperformed eukaryote-specific V4 primers in observed vs. expected abundance correlations and sequences with single mismatches to the primer were strongly underestimated (3-8 fold). A year of monthly time-series data from a protist-enriched 1.2-80 m size fraction yielded an average of 9% 18S, 17% chloroplast 16S, and 74% prokaryote 16S rRNA gene amplicons. These data demonstrate the potential for universal primers to generate quantitative and comprehensive microbiome profiles, although gene copy and genome size variability should be considered - as for any quantitative genetic analysis.

microbiology↗

bioRxiv2017

Taxon disappearance from microbiome analysis indicates need for mock communities as a standard in every sequencing run

Mock communities have been used in microbiome method development to help estimate biases introduced in PCR amplification, sequencing, and to optimize pipeline outputs. Nevertheless, the necessity of routine mock community analysis beyond initial method development is rarely, if ever, considered. Here we report that our routine use of mock communities as internal standards allowed us to discover highly aberrant and strong biases in the relative proportions of multiple taxa in a single Illumina HiSeqPE250 run. In this run, an important archaeal taxon virtually disappeared from all samples, and other mock community taxa showed >2-fold high or low abundance, whereas a rerun of those identical amplicons (from the same reaction tubes) on a different date yielded \"normal\" results. Although obvious from the strange mock community results, due to natural variation of microbiomes at our site, we easily could have missed the problem had we not used the mock communities. The \"normal\" results were validated over 4 MiSeqPE300 runs and 3 HiSeqPE250 runs, and run-to-run variation was usually low (Bray-Curtis distance was 0.12{+/-}0.04). While validating these \"normal\" results, we also discovered some mock microbial taxa had relatively modest, but consistent, differences between sequencing platforms. We suggest that using mock communities in every sequencing run is essential to distinguish potentially serious aberrations from natural variations. Such mock communities should have more than just a few members and ideally at least partly represent the samples being analyzed, to detect problems that show up only in some taxa, as we observed.\n\nImportanceDespite the routine use of standards and blanks in virtually all chemical or physical assays and most biological studies (a kind of \"control\"), microbiome analysis has traditionally lacked such standards. Here we show that unexpected problems of unknown origin can occur in such sequencing runs, and yield completely incorrect results that would not necessarily be detected without the use of standards. Assuming that the microbiome sequencing analysis works properly every time risks serious errors that can be avoided by the use of suitable mock communities.

microbiology↗