bioRxiv Science⌕ Search

Biology subjects

Ruan, D.

Publications and source records attributed to Ruan, D..

12 recordsLinked to original sources
bioRxiv2026

Expanding KitBase: Genome and Phenotype Integration of 3,268 Fast-Neutron Rice Mutants

Fast-neutron mutagenesis creates diverse genome-wide mutations, providing a powerful tool for crop functional genomics. Here, we present an expanded genomic and phenotypic analysis of 3,268 fast-neutron (FN)-induced mutant rice lines (Oryza sativa L. cv. Kitaake). All FN lines were whole-genome sequenced, and mutations were identified by alignment in the Nipponbare and KitaakeX reference genomes. We cataloged over 428,000 mutations affecting 78.49% of Nipponbare genes and 70.38% of KitaakeX genes. In silico expression analysis indicates that 575 non-mutated Nipponbare genes are highly expressed and likely essential for viability. Each mutant carries, on average, 68.5 mutations in the Nipponbare alignments or 63.2 mutations for KitaakeX alignments, distributed randomly across all 12 chromosomes with no evident hotspots. FN lines have approximately 8.5% fewer mutations when using the KitaakeX alignment, underscoring the unique contributions of each reference genome and the importance of utilizing both for comprehensive mutation discovery. The majority of mutations are small deletions and single-base substitutions, with deletions predominating in their effect on genes. We found that 74.4% of all transcription factor Nipponbare genes were mutated at least once. Phenotypic characterization of over 2,700 lines revealed a broad spectrum of variation in core agronomic traits (heading date, tiller number, plant height, panicle weight, seed yield components) and other morphological variants of interest. The integration of genomic and phenotypic data through the KitBase platform enabled the identification of candidate genes for several traits of interest. The KitBase website (https://kitbase.ucdavis.edu) has been updated to provide open access to all mutation data and seed stocks, as well as an intuitive query interface, facilitating forward and reverse genetic analyses in rice. This expanded resource enriches the rice functional genomics toolkit and highlights the value of coupling high-density mutation mapping with phenotypic data for rapid gene discovery and crop improvement.

plant biology↗
bioRxiv2025

Blood originates in hypoblasts during embryonic development

Blood is essential for oxygen supply throughout life. The emergence of blood in the human embryo remains poorly understood. Our study leverages multiple stem cell embryo models and advanced lineage barcoding to unveil that hypoblast, originally regarded as forming the yolk sac wall, is heterogeneous and contributes to CDX2+ extraembryonic mesoderm, followed by hemoglobin+ cells as the first blood cells. CDX2 marks the hypoblast-to-hemoglobin+ cell trajectory that functionally sustains oxygen levels in embryo models. These hemoglobin+ cells molecularly and functionally resemble phagocytes. We show that the erythro-core regulatory network is poised in hypoblasts, and its boost endows erythropoiesis to both hypoblasts and phagocytes. Hypoblasts are the origin of the first blood in humans and non-human primates, providing a conceptual framework that earlier blood generation than expected fills the gap in the establishment of circulation. Further, the hypoblast is a place where primates may repurpose the phagocyte program to carry oxygen throughout embryos. HighlightsO_LIBarcode-traced hypoblast fate in human embryo models; C_LIO_LIThe first blood comes from the hypoblast that contributes to hemoglobin+ phagocyte-like cells; C_LIO_LICDX2 marks hypoblast blood that sustains oxygen supply in embryos before heart formation; C_LIO_LIErythro-core regulatory network endows erythropoiesis to human hypoblasts and phagocytes. C_LI

developmental biology↗
bioRxiv2025

Generation of synthetic scRNA-seq-like transcriptomes using a generative adversarial network from RNA-seq data

Next-generation sequencing (NGS) technologies have become integral for high-throughput transcriptomic studies. Among these, single-cell RNA sequencing (scRNA-seq) is especially valuable for quantifying gene expression at the individual cell level, enabling the identification of rare cell populations and cellular differentiation pathways. However, the high cost of scRNA-seq often limits its broader application. Bulk RNA sequencing (RNA-seq) provides a more affordable alternative but lacks the single-cell resolution needed to elucidate cellular heterogeneity. Here, we present a cycle-consistent generative adversarial network (cycleGAN) approach to generate synthetic single-cell-like transcriptomes from bulk RNA-seq data. By adversarially training two sets of generators and discriminators, our framework attempts to learn the relationship between bulk and single-cell transcriptome distributions. Although this approach does not replace real scRNA-seq experiments, it can be a usefult tool to generate synthetic single-cell-like data for preliminary exploratory investigations and other machine learning applications. We further discuss the performance, limitations, and ethical considerations of our method.

bioinformatics↗
bioRxiv2025

CIP2A is required for mitotic recruitment of the SLX1/XPF/MUS81 tri-nuclease complex to replication stress-induced DNA lesions to maintain genome integrity

Perturbed DNA replication can lead to incompletely replicated DNA when cells enter mitosis and can interfere with chromosome segregation. Cells therefore require mechanisms to resolve these lesions during mitosis. The CIP2A-TOPBP1 complex is described to function as a molecular tether that connects fragmented DNA molecules. However, whether CIP2A also functions in processing of incompletely replicated DNA remained unclear. We show that CIP2A-TOPBP1 forms large filamentous structures at sites of incomplete DNA replication during mitosis, which recruit the SMX tri-nuclease complex members SLX4, MUS81 and ERCC1/XPF. These structures form in proximity to sites of mitotic DNA synthesis, although CIP2A is not required for mitotic DNA synthesis. In addition to its globular and coiled-coil domain, the unstructured C-terminal domain of CIP2A is essential for CIP2A-TOPBP1 filamentous structure formation and recruitment of the SMX complex. BRCA1-/- and BRCA2-/- cells have increased mitotic DNA lesions that recruit CIP2A and SLX4. We show that the C-terminal part of CIP2A is required for survival of BRCA2-/- cells. Moreover, SLX4 is crucial for genome stability in BRCA2-/- cells. Combined, we demonstrate that CIP2A-TOPBP1 recruits the SMX complex during mitosis, which is required to resolve mitotic DNA lesions, allows faithful chromosome segregation and maintain viability of BRCA2-/- cells.

cell biology↗
bioRxiv2024

Necessity and Impact of Specialization of Large Foundation Model for Medical Segmentation Tasks

BackgroundLarge foundation models, such as the Segment Anything Model (SAM), have shown remarkable performance in image segmentation tasks. However, the optimal approach to achieve true utility of these models for domain-specific applications, such as medical image segmentation, remains an open question. Recent studies have released a medical version of the foundation model MedSAM by training on vast medical data, who promised SOTA medical segmentation. Independent community inspection and dissection is needed. PurposeThis study assesses the performance of off-the-shelf medical foundation model MedSAM for the segmentation of anatomical structures in pelvic MR images. We also evaluate the dependency on prompting scheme and demonstrate the gain of further specialized fine-tuning. MethodsMedSAM and its lightweight version LiteMedSAM were evaluated out-of-the-box on a public MR dataset consisting of 589 pelvic images split 80:20 for training and testing. An nnU-Net model was trained from scratch to serve as a benchmark and to provide bounding box prompts for MedSAM. MedSAM was evaluated using different quality bounding boxes, those derived from ground truth labels, those derived from nnU-Net, and those derived from the former two but with 5-pixel isometric expansion. Lastly, LiteMedSAM was refined on the training set and reevaluated on this task. ResultsOut-of-the-box MedSAM and LiteMedSAM both performed poorly across the structure set, especially for disjoint or non-convex structures. Varying prompt with different bounding box inputs had minimal effect. The mean Dice score and mean Hausdorff distances (in mm) for obturator internus using MedSAM and LiteMedSAM were {0.251 {+/-} 0.110, 0.101 {+/-} 0.079} and {34.142 {+/-} 5.196, 33.688 {+/-} 5.306}, respectively. Fine-tuning of LiteMedSAM led to significant performance gain, improving Dice score and Hausdorff distance for the obturator internus to 0.864 {+/-} 0.123 and 5.022 {+/-} 10.684, on par with nnU-Net with no significant difference in evaluation of most structures. All segmentation structures all benefited significantly from specialized refinement, at varying improvement margin. ConclusionOur study alludes to the potential of deep learning models like MedSAM and lite MedSAM for medical segmentation but also highlight the need for specialized refinement and adjudication: it is quite likely that off-the-shelf use of such large foundation models may be suboptimal, and specialized fine-tuning can significantly enhance segmentation accuracy.

bioengineering↗
bioRxiv2024

SARS-CoV-2 infection activates inflammatory macrophages in vascular immune organoids

SARS-CoV-2 provokes devastating tissue damage by cytokine release syndrome and leads to multi-organ failure. Modeling the process of immune cell activation and subsequent tissue damage is a significant task. Organoids from human tissues advanced our understanding of SARS-CoV-2 infection mechanisms though, they are missing crucial components: immune cells and endothelial cells. This study aims to generate organoids with these components. We established vascular immune organoids from human pluripotent stem cells and examined the effect of SARS-CoV-2 infection. We demonstrated that infections activated inflammatory macrophages. Notably, the upregulation of interferon signaling supports macrophages role in cytokine release syndrome. We propose vascular immune organoids are a useful platform to model and discover factors that ameliorate SARS-CoV-2-mediated cytokine release syndrome.

immunology↗
bioRxiv2024

Multi-omic characterization of allele-specific regulatory variation in hybrid pigs

Genetic variation in the regulation of gene expression contributes substantially to phenotypic variation. Understanding how variation in DNA sequences and epigentic modifications leads to gene expression variation remains a challenging task. In hybrid animals where cellular environments are homogeneous, differences between the expression of paternal and maternal alleles must be due to cis sequence or epigenic differences. Therefore, hybrid mapping is a powerful approach to efficiently identify and characterize genes under regulation through mechanisms in cis. In this study, using reciprocal crosses of the phenotypically divergent Duroc and Lulai pig breeds, we performed a comprehensive multi-omic characterization of regulatory variation across brain, liver, muscle, and placenta in four developmental stages. We produced one of the largest multi-omic datasets to date in pigs, including 16 whole genome sequenced genomes, 48 whole genome bisulfite sequencing, 168 ATAC-Seq and 168 RNA-Seq samples. We developed a novel read count-based method to reliably assess allele-specific methylation, chromatin accessibility, and RNA expression. We showed that tissue specificity was much stronger than developmental stage specificity in all of DNA methylation, chromatin accessibility, and gene expression. We identified 573 genes showing allele specific expression, including those influenced by parent-of-origin as well as allele genotype effects. By integrating methylation, chromatin accessibility, and gene expression data, many of these allele specific expression can be explained by allele specific methylation and/or chromatin accessibility. This study provides one of the most comprehensive characterizations of regulatory variation across multiple tissues and developmental stages in pigs and offers new opportunity of genetic improvement for this important food animal species.

developmental biology↗
bioRxiv2022

MSdb: an integrated expression atlas of human musculoskeletal system

We introduce MSdb (https://www.msdb.org.cn), a database for visualization and integrated analysis of next-generation sequencing data from human musculoskeletal system, along with manually curated patient phenotype data. Systematic categorizing, standardized processing and freely accessible knowledge enables the reuse of public data. MSdb provides various types of analysis, including sample-level browsing of metadata information, gene/miRNA expression, and single-cell RNA-seq dataset. In addition, MSdb also allows integrated analysis for cross-samples and cross-omics analysis, including customized differentially-expressed gene/microRNA analysis, microRNA-gene network, scRNA-seq cross-sample/disease integration, and gene regulatory network analysis.

bioinformatics↗
bioRxiv2022

Nucleotide resolution genetic mapping in pigs by publicly accessible whole genome imputation

Genetic mapping to identify genes and alleles associated with or causing economically important quantitative trait variation in livestock animals such as pigs is a major goal in the genetic improvement animals. Despite recent advances in high throughput genotyping technologies, resolution of genetic mapping in pigs remains poor due in part to the low density of genotyped variant sites. In this study, we overcame this limitation by developing a reference haplotype panel for pigs based on 2,259 whole genome sequenced animals representing 44 pig breeds. We optimized the imputation procedure to achieve an average concordance rate in excess of 97%, non-reference concordance rate 91%, and r2 0.89. We demonstrated that genotype imputation using this resource can dramatically improve resolution of genetic mapping. Finally, we developed a public web server (swimgeno.org) to allow the pig genetics community to fully utilize this resource. We expect the resource and server to significantly facilitate genetic mapping and accelerate genetic improvement in pigs.

genomics↗
bioRxiv2017

Comprehensive Cell Type Specific Transcriptomics of the Human Kidney

The human kidney is a complex organ composed of specialized cell types. To better define this cellular complexity, we profiled the individual transcriptomes of 22,469 normal human kidney cells, identifying 27 cell types. We describe three distinct endothelial cell populations, a novel subset of intercalated cells, interstitial macrophage and dendritic cells, and identify numerous novel cell-type-specific markers, many validated using imaging mass cytometry and immunohistochemistry. Receptor-ligand analysis revealed previously unknown intercalated-endothelial and intercalated-distal nephron interactions, suggesting a role in maintenance of vascular integrity and intercalated cell survival. Notably, kidney disease-associated genes were largely expressed in proximal tubules, podocytes, endothelial and myeloid cells, highlighting an underappreciated role for endothelial cells in kidney pathologies. Our analysis also provides a resource of cell type enriched markers, solute carriers, channels and lncRNAs. In summary, this cell-type-specific transcriptome resource provides the foundation for a comprehensive understanding of kidney function and dysfunction at single cell resolution.

cell biology↗
bioRxiv2017

The Sequence of 1504 Mutants in the Model Rice Variety Kitaake Facilitates Rapid Functional Genomic Studies

The availability of a whole-genome sequenced mutant population and the cataloging of mutations of each line at a single-nucleotide resolution facilitates functional genomic analysis. To this end, we generated and sequenced a fast-neutron-induced mutant population in the model rice cultivar Kitaake (Oryza sativa L. ssp. japonica), which completes its life cycle in 9 weeks. We sequenced 1,504 mutant lines at 45-fold coverage and identified 91,513 mutations affecting 32,307 genes, 58% of all rice genes. We detected an average of 61 mutations per line. Mutation types include single base substitutions, deletions, insertions, inversions, translocations, and tandem duplications. We observed a high proportion of loss-of-function mutations. Using this mutant population, we identified an inversion affecting a single gene as the causative mutation for the short-grain phenotype in one mutant line with a small segregating population. This result reveals the usefulness of the resource for efficient identification of genes conferring specific phenotypes. To facilitate public access to this genetic resource, we established an open access database called KitBase that provides access to sequence data and seed stocks, enabling rapid functional genomic studies of rice.\n\nOne-sentence summaryWe have sequenced 1,504 mutant lines generated in the short life cycle rice variety Kitaake (9 weeks) and established a publicly available database, enabling rapid functional genomic studies of rice.

plant biology↗