Biology subjects

Dan, X.

Publications and source records attributed to Dan, X..

8 recordsLinked to original sources

bioRxiv2026

BioIMA: a one-click desktop tool for standardized extraction of phenotypic traits from biological images

Standardized extraction of quantitative phenotypes from images is increasingly important across plant biology, from ecological and evolutionary studies to genetics, breeding, and functional genomics. However, as large image datasets are increasingly used for trait analysis, many biologically relevant traits, including size, shape, color, and spatial patterning, are still measured manually or using fragmented semi-automated workflows. These limitations reduce throughput, reproducibility, and accessibility, especially for researchers without computational expertise. Here, we present BioIMA, an open-source desktop tool for rapid and standardized phenotyping from biological images. BioIMA integrates foundation model-based segmentation with automated trait computation, allowing users to extract quantitative measurements from images through an intuitive graphical interface and without model training. To validate its performance, we quantified a set of knot morphological traits in two Populus species, as these measurements are typically time-consuming to perform manually. Automatic measurements showed strong agreement with manual ImageJ-based measurements (R2 > 0.95), while reducing per-image processing time by approximately 75% (from ~15 s to ~4 s). BioIMA was further applied to diverse plant datasets, including Helianthus and Rhododendron images with varying morphologies and background conditions. Although developed for plant phenotyping, BioIMA may also be extended to other biological samples where region-based size, shape, or color traits are of interest. By combining accessibility and standardization in a lightweight local application, BioIMA provides a practical community resource for image-based phenotyping in ecological and evolutionary studies.

bioinformatics↗

bioRxiv2026

CMS: Achieving Uniform and High-Quality Sequencing across Challenging Non-canonical Genomic Regions

High-throughput sequencing is essential in modern biological research, yet low-complexity sequences remain challenging as they form structurally complex, non-canonical (non-B) DNA conformations that impede sequencing enzyme read-through. This leads to a long-standing trade-off: maximizing coverage introduces false positives (FP), while stringent filtering causes coverage loss and false negatives (FN). To address this, we developed CMS (Cross Mountains and Seas) on GeneMind sequencing platforms by optimizing its chemistry and enzymatic systems to traverse these secondary structures with high fidelity. Benchmarking across whole-genome (WGS) and whole-exome (WES) sequencing demonstrates that CMS addresses the trade-off by simultaneously enhancing both coverage uniformity and accuracy, notably achieving an approximately 100-fold reduction in low-coverage bins for WGS and a 70% reduction in FN insertions/deletions (INDELs) within complex non-B regions. Specifically, a synthetic G-quadruplex (G4) motif sequencing experiment demonstrates that CMS maintains a 1:1 strand ratio, effectively handling G4-induced biases where benchmarked platforms exhibit extensive depletion. These findings establish CMS as a reliable technology for the precise characterization of structural-challenging but functional-essential genome regions.

genomics↗

bioRxiv2025

Mitochondrial accumulation and lysosomal dysfunction result in mitochondrial plaques in Alzheimer's disease

Dysfunctional mitophagy is a key component of Alzheimers disease (AD) pathology, yet direct in vivo evidence and mechanistic insights remain limited. Using a mitophagy reporter in an AD mouse model (APP/PSEN1/mt-Keima), we identified mitochondrial plaques (MPs) composed of accumulated mitochondria within or outside lysosomes in AD, but not normal mouse brains. Similar structures were also found in AD human brains, but not in healthy controls. Abnormal mitochondrial accumulation in dystrophic neurites, defective mitophagy, and impaired lysosomal function disrupted proper mitochondrial degradation, resulting in excessive mitochondria accumulation both within and outside autophagic vesicles. The resulting intensive mitochondria-containing neurites coalesce into MPs, which co-develop with amyloid plaques to form mixed plaques. These findings establish MPs as novel pathological entity and a promising therapeutic target in AD.

cell biology↗

bioRxiv2024

Impaired online and enhanced offline motor sequence learning in individuals with Parkinson's disease

Whereas memory consolidation research has traditionally focused on longer temporal windows (i.e., hours to days) following an initial learning episode, recent research has also examined the functional significance of the shorter rest epochs commonly interspersed with blocks of task practice (i.e., "micro-offline" intervals on the timescale of seconds to minutes). In the motor sequence learning domain, evidence from young, healthy individuals suggests that micro-offline epochs afford a rapid consolidation process that is supported by the hippocampus. Consistent with these findings, amnesic patients with hippocampal damage were recently found to exhibit degraded micro-offline performance improvements. Interestingly, these offline losses were compensated for by larger performance gains during online practice. Given the known role of the striatum in online motor sequence learning, we hypothesized that individuals with dysfunction of the striatal system would exhibit impaired online, yet enhanced micro-offline, learning (i.e., a pattern of results opposite to those observed in patients with hippocampal lesions). We tested this hypothesis using Parkinsons disease (PD) as a model of striatal dysfunction. Forty-two drug-naive individuals (men and women) with a clinical diagnosis of unilateral PD and 30 healthy control subjects completed a motor sequence learning paradigm. Individuals with PD exhibited deficits during online task practice that were paralleled by greater improvements over micro-offline intervals. This pattern of results could not be explained by disease-related deficits in movement execution. These data suggest that striatal dysfunction disrupts online learning, yet total learning remains unchanged because of greater micro-offline performance improvements that potentially reflect hippocampal-mediated compensatory processes. Significance StatementThe short rest intervals commonly interspersed between periods of active task engagement have traditionally been employed to minimize the build-up of fatigue. There is recent evidence, however, suggesting that these rest epochs may play an active role in motor learning and memory processes and the hippocampus appears to be a critical brain region supporting this rapid "offline" learning. Here, we show that individuals with Parkinsons disease, a movement disorder characterized by dysfunction in the basal ganglia including the striatum, exhibit deficits during active task practice but greater learning over the interspersed offline intervals. Results potentially suggest that the relatively intact hippocampus may help compensate for motor sequence learning deficits linked to a disrupted striatal system in Parkinsons disease.

neuroscience↗

bioRxiv2023

The super-pangenome of Populus unveil genomic facets for adaptation and diversification in widespread forest trees

Understanding the underlying mechanisms between genome evolution and phenotypic and adaptive innovations is a key goal of evolutionary studies. Poplars are the worlds most widely distributed and cultivated trees, with extensive phenotypic diversity and environmental adaptability. Here we report a genus-level super-pangenome of 19 Populus genomes. After integrating pan-genomes with transcriptomes, methylomes and chromatin accessibility mapping, we reveal that the evolutionary fate of pan-genes and duplicated genes are largely associated with local genomic landscapes of regulatory and epigenetic architectures. Further comparative genomic analyses enabled to identify 142,202 structural variations (SVs) across species, which overlap with substantial genes and play key roles in both phenotypic and adaptive divergence. We experimentally validated a [~]180 bp presence/absence variant located in the promoter of the CUC2 gene, which contributed critically to leaf serration divergence between species. Together, this first super-pangenome resource in forest trees will not only accelerate molecular functional studies and genetic breeding of this globally important tree genus, but also lays a foundation for our understanding of tree biology.

evolutionary biology↗

bioRxiv2023

Chromosomal-level genome assembly of Populus lasiocarpa

Despite widespread biodiversity loss, our understanding of how species and populations will respond to accelerated climate change remains limited. In this study, we predict the evolutionary responses of Populus lasiocarpa, a key alpine forest tree species primarily found in the mountainous regions of a global biodiversity hotspot, to climate change. We accomplish this by generating and integrating a new reference genome for P. lasiocarpa, re-sequencing data for 200 samples, and gene expression profiles for leaf and root tissue following exposure to heat and waterlogging. Analyses of the re-sequencing data indicate that demographic dynamics, divergent selection, and long-term balancing selection have shaped and maintained genetic variation within and between populations over historical timescales. In examining genomic signatures of contemporary climate adaptation, we found that haplotype blocks, characterized by inversion polymorphisms that suppress recombination, play a crucial role in clustering environmentally adaptive variations. Comparison of evolved and plastic gene expression show that genes with expression plasticity generally align with evolved responses, highlighting the adaptive role of plasticity. Lastly, we incorporated local adaptation, migration, genetic load, and plasticity responses into our predictions of population-level climate change risks. Our findings reveal that western populations, primarily distributed in the Hengduan Mountains--a region known for its environmental heterogeneity and significant biodiversity--are the most vulnerable to climate change and should be prioritized for conservation and management. Overall, our study advances understanding of the relative roles of long-term natural selection, local environmental adaptation, and immediate plasticity responses in driving evolutionary adaptation to climate change in keystone species.

genomics↗

bioRxiv2023

Chromosomal-level genome assembly of Populus adenopoda

High-quality reference genomes for several species have promoted breeding and functional studies of poplar trees. By resequencing numerous accessions of these and closely related species, single nucleotide polymorphisms (SNPs) and small insertion/deletions (InDels) have been identified to assist in clarifying local adaptation and phenotypic diversification. A chromosome-level genome assembly for P. adenopoda was assembled based on Illumina and PacBio sequencing platforms, facilitated by Hi-C technology. The assembled genome size was about 383 Mb, with 99.70% of the contigs anchored to 19 pseudo-chromosomes, and a total of 33,505 protein-coding genes were annotated. This high-quality genome provided the genomic basis for the subsequent detection of various variants.

genomics↗

bioRxiv2022

Genomic insights into present local adaptation and future climate change vulnerability of a keystone forest tree species in East Asian

Rapid global climate change is posing a huge threat to biodiversity. Assessments of the adaptive capacity for most taxa is usually performed on the species as a whole, but fails to incorporate intraspecific adaptive variation that may play a fundamental role in buffering future shifting climates. Here we generate a chromosome-scale genome assembly for Populus koreana, a pioneer and keystone tree species in East Asia temperate forests. We also obtain whole-genome sequences of 230 individuals collected from 24 natural populations. An integration of population genomics and environmental variables was performed to reveal the genomic basis of local adaptation to diverse climate variable. We identify a set of climate-associated single nucleotide polymorphisms (SNPs), insertions-deletions (Indels) and structural variations (SVs), in particular numerous adaptive non-coding variants distributed across the genome of P. koreana. We incorporate these variants into an environmental modelling scheme to predict spatiotemporal responses of P. koreana to future climate change. Our results highlight the insights that the integration of genomic and climate data can shed on the future evolutionary adaptive capacities of a species to changing environmental conditions.

evolutionary biology↗