Biology subjects

Kong, N.

Publications and source records attributed to Kong, N..

9 recordsLinked to original sources

bioRxiv2026

Leveraging Human Pangenome for Improved Somatic Variant Detection

Somatic variant detection is technically challenging due to low variant allele fractions, the confounding presence of germline variation, and reference bias. Linear references such as GRCh38 miss sample-specific variation, causing misalignments and incorrect variant calls. Although telomere-to-telomere donor-specific assemblies (DSAs) accurately represent individual genomes, their application is limited by cost and technical barriers. Alternatively, the graph-based human pangenome provides a scalable framework to improve read alignment and perform genome inference. Here, we benchmarked somatic variant detection using GRCh38, graph-based pangenomes, and pangenome-inferred DSAs with a HapMap mixture dataset and the COLO829 melanoma cell line. Pangenome-guided alignment improves read mapping and somatic variant calling accuracy. Furthermore, personalized pangenomes partially reconstruct donor-specific genomic content, improving accuracy, reducing germline contamination, and enabling detection of events in loci absent or poorly represented in GRCh38. These findings demonstrate that graph-based and personalized pangenomes are effective strategies for enhancing somatic variant detection compared with GRCh38.

genomics↗

bioRxiv2025

Himito: a Graph-based Toolkit for Mitochondrial Genome Analysis using Long Reads

Understanding the genetic and epigenetic regulation of mitochondrial DNA (mtDNA) is essential for elucidating mechanisms of aging and disease. Long-read sequencing can span the entire mitochondrial genome and directly capture base-modification signals, yet analytical tools for such data remain limited. We developed Himito, a graph-based toolkit for analyzing mitochondrial genome using long reads. Himito filters reads originating from nuclear mitochondrial insertions (NUMTs), constructs a sequence graph to represent mtDNA diversity, assembles primary haplotypes, calls variants, and analyzes 5-methylcytosine (5mC) modifications within a unified framework. Benchmarking on high-quality reference datasets shows Himito achieves superior performance in assembly and variant calling compared with existing tools. Applied to the All of Us (AoU) v8 dataset, Himito identified pathogenic mtDNA variants, revealed population-scale haplogroup diversity, and uncovered age-related genetic and epigenetic patterns. These results demonstrate that long-read sequencing, combined with graph-based analysis, enables integrated characterization of mitochondrial genomic and epigenomic variation. Himito is available at https://github.com/broadinstitute/Himito.

bioinformatics↗

bioRxiv2025

A Pangenomic Method for Establishing a Somatic Variant Detection Resource in HapMap Mixtures

Somatic mosaicism is essential in human biology and disease, yet robust benchmarks are scarce. The SMaHT Consortium mixed six HapMap cell lines to create artificial somatic variants spanning 0.25% to 16.5% variant allele fractions. We developed a technology-agnostic method that builds pangenome graphs from individual assemblies to create unified benchmarking sets: > 6M single-nucleotide variants, 1.8M small insertions/deletions, 49K structural variations, and 10K mobile element insertions across autosomes, X, and mitochondrial chromosomes. We validated the variants using ultra-deep simulated reads and developed a binomial-based model to estimate coverage requirements for variant detection. Evaluating multiple callers showed CHM13 alignment improves structural variant detection and offers advantages in difficult-to-map regions compared to GRCh38. Systematic characterization showed regions with low detection rate are enriched in centromeres, satellite sequences, tandem repeats, and falsely duplicated genes. This accurate, versatile resource enables systematic evaluation of somatic variant detection technologies.

genomics↗

bioRxiv2025

SnakeAltPromoter Facilitates Differential Alternative Promoter Analysis

BackgroundAlternative promoter usage regulates isoform diversity in mammals, playing critical roles in development, disease, and cellular reprogramming. While Cap Analysis of Gene Expression (CAGE) enables precise transcription start site mapping, its high cost and limited coverage hinder scalability. In contrast, RNA-seq is abundant across biological contexts; several algorithms (ProActiv, Salmon, DEXSeq) infer promoter activity from these data, yet no unified, reproducible framework exists to execute, benchmark, and compare them or to scale alternative promoter analyses across large compendia. ResultsWe developed snakeAltPromoter, an end-to-end Snakemake workflow that ingests raw FASTQ files, performs quality control and alignment, quantifies promoter activity using three complementary strategies (junction-based, transcript-based, and first-exon-based), classifies promoters into major, minor/alternative, and inactive categories, and conducts both differential promoter activity and usage analysis. Crucially, snakeAltPromoter integrates a systematic benchmarking module against matched CAGE profiles to reveal method-specific strengths and limitations. ProActiv showed the highest concordance with CAGE in promoter classification, activity and differential analysis, Salmon was robust at low coverage and intronless cases. Overall, the complete workflow recovered a majority of CAGE-validated active promoters and processed a 50 M-read RNA-seq sample in around 2h on a 32-core node, demonstrating both accuracy and scalability. ConclusionssnakeAltPromoter is, to our knowledge, the first reproducible framework that pairs comparative method evaluation with scalable differential alternative promoter analysis. It provides concrete guidance for method selection under different experimental scenarios and enables high-throughput mining of promoter-level regulation from public RNA-seq repositories. Code and example data are freely available at https://github.com/YidanSunResearchLab/SnakeAltPromoter.git.

bioinformatics↗

bioRxiv2025

BioinAI: a general bioinformatic framework for multi-level transcriptomic data analysis using multiple semi-agents

Clinical and biological insights from large-scale transcriptomic data are often limited by technical variability and analytical complexity. Here, we introduce BioinAI, a general bioinformatic framework designed for multi-level transcriptomic data analysis. As part of the BioinAI framework, two algorithms named DeepAdvancer and stNiche were developed to improve data integration and analytical efficiency. DeepAdvancer leverages a class-aware adversarial autoencoder to reconstruct gene-expression profiles from 49,738 samples across 131 skin conditions. These profiles revealed a conserved inflammatory axis and a transcriptomic continuum which link diverse diseases through shared immune responses and structural programs. stNiche leverages spatial graph networks and symmetry-aware matching to identify functional cellular niches and reveals microstructural alterations across development, homeostasis, and disease. For instance, it identified a fibroblast-immune niche surrounding hair follicles in healthy skin, which disappears in pathological states. In addition, BioinAI provides a user-friendly online analysis platform powered by multiple semi-agents (www.bioinai.com), significantly facilitating the extraction of biological insights to advance scientific research.

bioinformatics↗

bioRxiv2024

In vivo engineered quadrivalent CAR-macrophages break tumor barrier,remodel TME and overcome tumor heterogeneity through antigen spreading

CAR-macrophages have shown promising prospect in treating solid tumors. Ex vivo engineered CAR-macrophages face the challenge of low transfection efficiency, long preparation cycle, and limited cell number. Here, we designed two novel CAR molecules, GPC3-CAR-Super IL-2 and FAP-CAR-{bigtriangleup}TGF{beta}RII from the perspective of targeting tumor cells and improving tumor microenvironment, and generated quadrivalent CAR-macrophages in vivo for treating solid tumors by the LNP-mRNA system. We found that in vivo engineered quadrivalent CAR-macrophages can strongly activate tumor immunity and achieve complete tumor regression without significant side effects. Mechanically, in vivo engineered quadrivalent CAR-macrophages broke down physical barriers around the tumor constructed by CAFs and significantly promoted infiltration and expansion of CD8+ T cells. Moreover, the transiently formed CAR-macrophages in vivo are sufficient to form long-lasting T cell memory which can effectively prevent tumor recurrence. Most importantly, in vivo engineered CAR-macrophages also stimulated T cell memory against antigen-negative tumor cells through antigen spreading, which might effectively prevent the immune escape of heterogeneous tumor cells. Overall, we developed a platform of in vivo CAR-macrophages with dual roles as a tumor-killing effector cell and a recurrence-preventing vaccine.

bioengineering↗

bioRxiv2020

Monitoring the microbiome for food safety and quality using deep shotgun sequencing

In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera per HPP sample on average with 65 genera present in all samples. The most abundant of these were Bacteroides, Clostridium, Lactococcus, Aeromonas, and Citrobacter. We also observed shifts in the microbial community corresponding to ingredient composition differences. When comparing culture-based results for Salmonella with total RNA sequencing, we found that Salmonella growth did not correlate with multiple sequence analyses. We conclude that microbiome sequencing is useful to characterize complex food microbial communities, while additional work is required for predicting specific species viability from total RNA sequencing.

microbiology↗

bioRxiv2020

Genomic characterization of a diazotrophic microbiota associated with maize aerial root mucilage

A geographically isolated maize landrace cultivated on nitrogen-depleted fields without synthetic fertilizer in the Sierra Mixe region of Oaxaca, Mexico utilizes nitrogen derived from the atmosphere and develops an extensive network of mucilage-secreting aerial roots that harbors a diazotrophic microbiota. Targeting these diazotrophs, we selected nearly 600 microbes from a collection isolated from these plants and confirmed their ability to incorporate heavy nitrogen (15N2) metabolites in vitro. Sequencing their genomes and conducting comparative bioinformatic analyses showed that these genomes had substantial phylogenetic diversity. We examined each diazotroph genome for the presence of nif genes essential to nitrogen fixation (nifHDKENB) and carbohydrate utilization genes relevant to the mucilage polysaccharide digestion. These analyses identified diazotrophs that possessed canonical nif gene operons, as well as many other operon configurations with concomitant fixation and release of >700 different 15N labeled metabolites. We further demonstrated that many diazotrophs possessed alternative nif gene operons and confirmed their genomic potential to derive chemical energy from mucilage polysaccharide to fuel nitrogen fixation. These results confirm that some diazotrophic bacteria associated with Sierra Mixe maize were capable of incorporating atmospheric nitrogen into their small molecule extracellular metabolites through multiple nif gene configurations while others were able to fix nitrogen without the canonical (nifHDKENB) genes. Data SummaryGenetic resources, including biological materials and nucleic acid sequences, were accessed under an Access and Benefit Sharing (ABS) Agreement between the Sierra Mixe community and the Mars Corporation, and with authorization from the Mexican government. An internationally recognized certificate of compliance has been issued by the Mexican government under the Nagoya Protocol for such activities (ABSCH-IRCC-MX-207343-3). Any party seeking access to the nucleic acid sequences underlying the analysis reported here is subject to the full terms and obligations of the ABS agreement and the authorization from the government of Mexico. Individuals wishing to access nucleic acid sequence data for scientific research activities should contact Mars Incorporated Chief Science Officer at CSO@effem.com.

genomics↗

bioRxiv2019

Salmonella Enhances Osteogenic Differentiation in Adipose-Derived Mesenchymal Stem Cells

The potential of mesenchymal stem cells (MSCs) for tissue repair and regeneration has garnered great attention. While MSC interaction with microbes at sites of tissue damage and inflammation is likely, especially in the gut, the consequences of bacterial association have yet to be elucidated. This study investigated the effect of Salmonella enterica ssp enterica serotype Typhimurium on MSC trilineage differentiation path and mechanism. Through examination of key markers of differentiation, immunomodulatory regulators, and inflammatory cytokines, we demonstrated that Salmonella altered osteogenic and chondrogenic differentiation pathways in human and goat adipose-derived MSCs. Gene expression profiles defined signaling pathway alterations in response to Salmonella association not observed in epithelial cells. We uncovered significant differential expression (P < 0.05) of genes associated with anti-apoptotic and pro-proliferative responses in MSCs during Salmonella challenge. These observations led us to conclude that bacteria, specifically Salmonella, induce pathways that influence functional differentiation trajectories in MSCs, thus implicating substantial microbial influence on MSC physiology and immune activity.

microbiology↗