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PubMed2025

Chromosome scale genomes of two invasive Adelges species enable virtual screening for selective adelgicides.

Two invasive hemipteran adelgids are associated with widespread damage to several North American conifer species. Adelges tsugae, hemlock woolly adelgid, was introduced from Japan and reproduces parthenogenetically in North America, where it has rapidly decimated Tsuga canadensis and Tsuga caroliniana (the eastern and Carolina hemlocks, respectively). Adelges abietis, eastern spruce gall adelgid, introduced from Europe, forms distinctive pineapple-shaped galls on several native spruce species. While not considered a major forest pest, it weakens trees and increases susceptibility to additional stressors. Broad-spectrum insecticides that are often used to control adelgid populations can have off-target impacts on beneficial insects. Whole genome sequencing was performed on both species to aid in development of targeted solutions that may minimize ecological impact. Adelges abietis was sequenced using Illumina Linked-Read technology from 30 pooled individuals, with Hi-C scaffolding performed using data from a single individual collected from the same host plant. Adelges tsugae used Oxford Nanopore long-read sequencing from pooled nymphs. The assembled A. tsugae and A. abietis genomes, pooled from several parthenogenetic females, are 220.75 Mbp and 253.16 Mbp, respectively. Each consists of eight autosomal chromosomes, as well as two sex chromosomes (X1/X2), supporting the XX-XO sex determination system. The genomes are over 96% complete based on BUSCO assessment. Genome annotation identified 11,424 and 12,060 protein-coding genes in A. tsugae and A. abietis, respectively. Comparative analysis of proteins across 29 hemipteran species and 14 arthropod outgroups identified 31,666 putative gene families. Gene family evolution analysis with CAFE revealed lineage-specific expansions in immune-related aminopeptidases (ERAP1) and juvenile hormone binding proteins (JHBP), contractions in juvenile hormone acid methyltransferases (JHAMT), and conservation of nicotinic acetylcholine receptors (nAChR). These genes were explored as candidate families towards a long-term objective of developing adelgid-selective insecticides. Structural comparisons of proteins across seven focal species (Adelges tsugae, Adelges abietis, Adelges cooleyi, Rhopalosiphum maidis, Apis mellifera, Danaus plexippus, and Drosophila melanogaster) revealed high conservation of nAChR and ERAP1, while JHAMT exhibited species-specific structural divergence. The potential of JHAMT as a lineage-specific target for pest control was explored through virtual drug and pesticide screening.

adelgids↗
PubMed2025

CNV-Finder: Streamlining Copy Number Variation Discovery.

Copy Number Variations (CNVs) play pivotal roles in the etiology of complex diseases and are variable across diverse populations. Understanding the association between CNVs and disease susceptibility is significant in disease genetics research and often requires analysis of large sample sizes. One of the most cost-effective and scalable methods for detecting CNVs is based on normalized signal intensity values, such as Log R Ratio (LRR) and B Allele Frequency (BAF), from Illumina genotyping arrays. In this study, we present CNV-Finder, a novel pipeline integrating deep learning techniques on array data, specifically a Long Short-Term Memory (LSTM) network, to expedite the large-scale identification of CNVs within predefined genomic regions. This facilitates efficient prioritization of samples for time-consuming or costly subsequent analyses such as Multiplex Ligation-dependent Probe Amplification (MLPA), short-read, and long-read whole genome sequencing. We incorporate four genes to establish our methods-Parkin (PRKN), Leucine Rich Repeat And Ig Domain Containing 2 (LINGO2), Microtubule Associated Protein Tau (MAPT), and alpha-Synuclein (SNCA)-which may be relevant to neurological diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Progressive Supranuclear Palsy (PSP), or related disorders such as essential tremor (ET). By training our models on expert-annotated samples and validating them across diverse cohorts, including those from the Global Parkinson's Genetics Program (GP2) and additional dementia-specific databases, we demonstrate the efficacy of CNV-Finder in accurately detecting deletions and duplications. Our pipeline outputs app-compatible files for visualization within CNV-Finder's interactive web application. This interface enables researchers to review predictions and filter displayed samples by model prediction values, LRR range, and variant count in order to explore or confirm results. Our pipeline integrates this human feedback to enhance model performance and reduce false positive rates. Through a series of comprehensive analyses and validations using visual inspection, MLPA, short-read, and long-read sequencing data, we demonstrate the robustness and adaptability of CNV-Finder in identifying CNVs with regions of varied size, probe density, and noise. Our findings highlight the significance of contextual understanding and human expertise in enhancing the precision of CNV identification, particularly in complex genomic regions like 17q21.31. The CNV-Finder pipeline is a scalable, publicly available resource for the scientific community, available on GitHub (https://github.com/GP2code/CNV-Finder; DOI 10.5281/zenodo.14182563). CNV-Finder not only expedites accurate candidate identification but also significantly reduces the manual workload for researchers, enabling future targeted validation and downstream analyses in regions or phenotypes of interest.

Copy Number Variation (CNV)↗
PubMed2025

CASTER-DTA: Equivariant Graph Neural Networks for Predicting Drug-Target Affinity.

Accurately determining the binding affinity of a ligand with a protein is important for drug design, development, and screening. With the advent of accessible protein structure prediction methods such as AlphaFold, predicted protein 3D structures are readily available; however, methods for predicting binding affinity currently do not take full advantage of 3D protein information. Here, we present CASTER-DTA (Cross-Attention with Structural Target Equivariant Representations for Drug-Target Affinity), which uses an equivariant graph neural network to learn more robust protein representations alongside a standard graph neural network to learn molecular representations to predict drug-target affinity. We augment these representations by incorporating an attention-based mechanism between protein residues and drug atoms to improve interpretability. We show that CASTER-DTA represents a state-of-the-art improvement on multiple benchmarks for predicting drug-target affinity and that it generates novel insights for several related tasks. We then apply CASTER-DTA to create a large resource of the binding affinities of every FDA-approved drug against every protein in the human proteome and make these predictions freely available for download. We also make available a web server for researchers to apply a pretrained CASTER-DTA model for predicting binding affinities between arbitrary proteins and drugs.

deep learning↗
PubMed2025

Multivariate genetic of 2.2 million individuals demonstrate genetic influences on substance use disorders operate via behavioral disinhibition and substance-specific risk.

Ongoing efforts to identify genes involved in substance use disorders (SUDs) often focus on individual disorders despite high rates of co-occurrence with each other and other externalizing traits. Here, we investigate whether incorporating data on other externalizing traits can boost power to detect without sacrificing specificity of SUD genetic signal. We used multivariate genomic analyses and downstream biological annotation and genetic association analyses to explore this question. We found that joint analysis of SUDs and other externalizing traits resulted in increased insights into the neurobiology of broad and substance-specific SUD risk. We found no evidence of loss of specificity for SUD genetic signal but note improvements in our ability to characterize the neurobiology of broad and substance-specific SUD genetic effects. Our findings suggest that genetic risk for SUDs operates largely via pathways shared with other behaviors characterized by behavioral disinhibition, with additional substance-specific risk, and that modeling this shared disposition improves gene discovery.

Journal Article↗
PubMed2025

Alevin-fry-atac enables rapid and memory frugal mapping of single-cell ATAC-seq data using virtual colors for accurate genomic pseudoalignment.

Ultrafast mapping of short reads via lightweight mapping techniques such as pseudoalignment has significantly accelerated transcriptomic and metagenomic analyses, often with minimal accuracy loss compared to alignment-based methods. However, applying pseudoalignment to large genomic references, like chromosomes, is challenging due to their size and repetitive sequences. We introduce a new and modified pseudoalignment scheme that partitions each reference into "virtual colors…. These are essentially overlapping bins of fixed maximal extent on the reference sequences that are treated as distinct "colors" from the perspective of the pseudoalignment algorithm. We apply this modified pseudoalignment procedure to process and map single-cell ATAC-seq data in our new tool alevin-fry-atac . We compare alevin-fry-atac to both Chromap and Cell Ranger ATAC . Alevin-fry-atac is highly scalable and, when using 32 threads, is approximately 2.8 times faster than Chromap (the second fastest approach) while using approximately one third of the memory and mapping slightly more reads. The resulting peaks and clusters generated from alevin-fry-atac show high concordance with those obtained from both Chromap and the Cell Ranger ATAC pipeline, demonstrating that virtual colorenhanced pseudoalignment directly to the genome provides a fast, memory-frugal, and accurate alternative to existing approaches for single-cell ATAC-seq processing. The development of alevin-fry-atac brings single-cell ATAC-seq processing into a unified ecosystem with single-cell RNA-seq processing (via alevin-fry ) to work toward providing a truly open alternative to many of the varied capabilities of CellRanger . Furthermore, our modified pseudoalignment approach should be easily applicable and extendable to other genome-centric mapping-based tasks and modalities such as standard DNA-seq, DNase-seq, Chip-seq and Hi-C.

Journal Article↗
PubMed2025

BioMedGraphica: An All-in-One Platform for Joint Textual Biomedical Prior Knowledge and Numeric Graph Generation.

Multi-omic data analysis is essential for scientific discovery in precision medicine. However, translating statistical results of omic data analysis into novel scientific hypothesis remains a significant challenge. Human experts must manually review analysis results and generate new hypothesis based on extensive and inter-connected biomedical prior knowledge, which is subjective and not scalable. While large language models (LLMs) can accelerate the discovery, their reasoning improves when grounded in structured, auditable and comprehensive biomedical prior knowledge. Biomedical knowledge, however, is scattered across heterogeneous databases that use diverse and inconsistent nomenclature systems, making it difficult to integrate resources into a unified format for scalable analysis. This fragmentation limits the ability of AI systems to fully leverage biomedical data for scientific discovery. To address these challenges, we developed BioMedGraphica , an all-in-one platform that harmonizes fragmented biomedical resources by integrating 11 entity types and 30 relation types from 43 databases into a unified knowledge graph containing 2,306,921 entities and 27,232,091 relations. In addition, to the best of our knowledge, this is the first work to propose a novel Textual-Numeric Graph (TNG) data-structure for multi-omics data analysis. In TNG, textual information captures prior biological knowledge (e.g., transcription start sites, functions, mechanisms), while numeric values represent quantitative biomedical features, and the integrated relations can help uncover mechanisms. By bridging prior knowledge with user-specific data, TNG is a novel and ideal data-structure for the development of graph foundation models, with the potential to improve prediction performance and interpretability, while also augmenting LLMs by supplying graph-structured mechanistic context to strengthen reasoning. The details for BioMedGraphica code can be accessed by github link: https://github.com/FuhaiLiAiLab/BioMedGraphica and BioMedGraphica knowledge graph data can be downloaded from huggingface dataset: https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica.

biomedical knowledge graph↗
PubMed2025

Polygenic Risk Factors for Comorbid Diagnoses in Individuals with Substance Use Disorders: A Phenome-Wide Survival Analysis.

OBJECTIVE: Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome wide association studies (PheWAS). However, PheWAS are largely cross-sectional, limiting our understanding of whether diagnoses predate development of an SUD. We characterize whether polygenic scores (PGS) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. METHODS: Using data from All of Us (N = 393,596), we explored: 1) whether social determinants of health (SDoH) are associated with lifetime risk of SUD (N cases = 42,568) and 2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, post-traumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. RESULTS: Multiple SDoH were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g., <$10K annually vs $100K-$150K annually: OR = 3.89, 95% CI = 3.66, 4.13). There were 101 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, post-traumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. CONCLUSIONS: Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGS for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Journal Article↗
PubMed2025

A general strategy for generating expert-guided, simplified views of ontologies.

Annotation of biomedical entities with widely used, well-structured ontologies and ontology-aware tools ensures data and analyses are Findable, Accessible, Interoperable, and Reusable (FAIR). Standardized terms with synonyms support lexical search, while ontology structure enables biologically meaningful grouping of annotations, such as by location and type. However, ontologies serving diverse communities are often more complex than needed for specific applications, creating barriers to adoption by researchers and resource developers. For example, cell atlases often attempt simplifications by manually building term hierarchies linking to cell type and anatomy ontologies, but these may include relationship types unsuitable for grouping annotations. We present tools for validating human expert curated term hierarchies, developed in two human reference atlas projects, against ontology structures. The tools provide tabular statistics plus graphical views of matching and non-matching terms and relationships to support discussion and conflict resolution. The HuBMAP Human Reference Atlas (HRA) effort is used to validate the approach and tools, and the Human Developmental Cell Atlas is featured as a use case.

Journal Article↗
PubMed2025

Ketone body mediated histone &#x3b2;-hydroxybutyrylation is reno-protective.

Starvation, intermittent fasting and exercise, all of which are recommended lifestyle modifiers share a common metabolic signature, ketogenesis to generate the ketone bodies, predominantly &#x3b2;-hydroxybutyrate. &#x3b2;-hydroxybutyrate exerts beneficial effects across various contexts, preventing or mitigating disease. We hypothesized that these dynamic health benefits of &#x3b2;-hydroxybutyrate might stem from its ability to regulate genome architecture through chromatin remodeling via histone &#x3b2;-hydroxybutyrylation, thereby influencing the transcriptome. Focusing on the kidney, which is an end organ protected by &#x3b2;-hydroxybutyrate, we examined histone &#x3b2;-hydroxybutyrylation-mediated chromatin remodeling. Notably, regions of the genome associated with lipid catabolism were predominantly in an open chromatin configuration, leading to active transcription and translation. Significant &#x3b2;-hydroxybutyrylation was observed in the kidneys and the most highly upregulated gene actively transcribed and translated was 3-hydroxy-3-methyglutaryl CoA Synthase 2 (Hmgcs2), a gene responsible for the biosynthesis of &#x3b2;-hydroxybutyrate in mitochondria. In contrast, regions with more compact chromatin structures were enriched with genes related to immune function such as protein tyrosine phosphatase receptor type C (Ptprc) and lymphocyte cytosolic protein 1 (Lcp1), which exhibited reduced transcription and translation. These results reveal that renal epigenetic histone &#x3b2;-hydroxybutyrylation is a novel mechanism by which transcriptional regulation of both energy metabolism and immune function occur concomitantly to protect kidneys and lower hypertension.

Blood pressure↗
PubMed2025

A personalized multi-platform assessment of somatic mosaicism in the human frontal cortex.

Somatic mutations in individual cells create genomic mosaicism, influencing genetic disorders and cancers. While clonal mutations in cancers are well-studied, rarer somatic variants in normal tissues remain poorly characterized. This study systematically evaluates detection methods using a personalized donor-specific assembly (DSA) from a neurotypical individual's dorsolateral prefrontal cortex assessed with Oxford Nanopore, NovaSeq, linked-read sequencing, Cas9-targeted long-read sequencing (TEnCATS), and single-neuron MALBAC amplification. The haplotype-resolved DSA improved cross-platform analysis, dramatically increasing phasing rates. Germline SNVs, structural variations (SVs), and transposable elements (TEs) were recalled with 99.4%-99.7% accuracy in bulk tissue, and phased haplotype analysis reduced false positives by 15.4%-75.1% for putative somatic candidates. Long-read single-neuron sequencing detected nine somatic SV candidates, demonstrating enhanced sensitivity for rare variants, while TEnCATS identified eight low-frequency somatic TE candidates. These findings highlight advanced methodologies for precise somatic variant detection, critical for understanding mosaicism's role in health and disease.

Multi-platform Sequencing↗
PubMed2025

Replication stress increases de novo CNVs across the malaria parasite genome.

Changes in the copy number of large genomic regions, termed copy number variations (CNVs), contribute to important phenotypes. CNVs are readily identified using conventional approaches when present in a large fraction of the cell population. However, CNVs in only a few genomes are often overlooked but important; if beneficial, a de novo CNV that arises in a single genome can expand during selection to create a population of cells with novel characteristics. While single cell methods for studying de novo CNVs are increasing, we continue to lack information about CNV dynamics in rapidly evolving microbial populations. Here, we investigated de novo CNVs in the genome of the Plasmodium parasite that causes human malaria. The highly AT-rich P. falciparum genome readily accumulates CNVs that facilitate rapid adaptation. We employed low-input genomics and specialized computational tools to evaluate the impact of sub-lethal stress on the de novo CNV rate. We observed a significant increase in genome-wide de novo CNVs following treatment with an antimalarial compound that inhibits replication. De novo CNVs encompassed genes from various cellular pathways participating in human infection. This snapshot of CNV dynamics emphasizes the connection between replication stress, DNA repair, and CNV generation in this important microbial pathogen.

Journal Article↗
PubMed2026

Linkage between HLA-B8 and HLA-DQ2.5 Contributes to Ancestry-Dependent Genetic Risk for Celiac Disease.

BACKGROUND: Most genetic studies on celiac disease (CeD) have focused on individuals of European descent. Limited data are available for the Hispanic and black populations. METHODS: We analyzed whole-genome sequencing data, electronic health records (EHR), and laboratory results from the All of Us Research Program. We identified 3,481 individuals with CeD through EHR, self-reporting, or both. Of these, 2,899 carried one of the four well-established risk haplotypes, including 262 of admixed American (89% Hispanic) and 108 of African (70% black) ancestry. Five sex-, age-, and ancestry-matched controls per case were selected for the assessment of genetic and clinical risk factors. RESULTS: An enrichment in the DQB1*02:01 allele was observed in CeD patients across all ancestries, with the strongest association in Europeans (32.3% vs. 11.6%), followed by Americans (18.5% vs. 8.1%) and Africans (15.7% vs. 8.1%). Among individuals carrying the DQ2.5 (DQA1*05:01-DQB1*02:01 haplotype), HLA-B8 was present in 72.3% of Europeans, 42.3% of Admixed Americans, and lower in Africans. This linkage disequilibrium was higher in CeD patients than in controls across all three ancestries. A polygenic risk score distinguished seropositive CeD from controls with 86% accuracy. Incorporating clinical risk factors, including family history, hypothyroidism, diarrhea, vitamin D deficiency, and anemia, increased predictive accuracy to 92%. The model identified 93% of CeD patients with tTG-IgA levels greater than 10 IU/mL. CONCLUSION: Linkage between HLA-B8 and DQ2.5 differs significantly among individuals of European, admixed American, and African ancestry, contributing to ancestry-dependent genetic risk for CeD.

Celiac disease↗
PubMed2025

Short activation domains control chromatin association of transcription factors.

Transcription factors regulate gene expression with DNA-binding domains (DBDs) and activation domains. Despite mounting evidence to the contrary, it is frequently assumed that DBDs are solely responsible for interacting with DNA and chromatin. Here, we used single-molecule tracking of transcription factors in living cells to show that short activation domains can control the fraction of molecules bound to chromatin. Stronger activation domains have higher bound fractions and longer residence times on chromatin. Furthermore, mutations that increase activation domain strength also increase chromatin binding. This trend was consistent in four different activation domains and their mutants. This effect further held for activation domains appended to three different structural classes of DBDs. Stronger activation domains with high chromatin-bound fractions also exhibited increased binding to the p300 coactivator in proximity-assisted photoactivation experiments. Taken together, these results suggest that activation domains play a major role in tethering transcription factors to chromatin, challenging the traditional view that the DBD is the sole driver of genome binding.

Journal Article↗
PubMed2025

Spatially ordered zygotic genome activation fulfills embryo quality control.

Early embryo development features autonomous, maternally-driven cell divisions that self- organize the multicellular blastula or blastocyst tissue. Maternal control cedes to the zygote starting with the onset of widespread zygotic genome activation (ZGA), which is essential for subsequent cell fate determination and morphogenesis. Intriguingly, although the onset of ZGA is highly regulated at the level of an embryo, it can be non-homogenous and precisely patterned at the single-cell level. We previously demonstrated a stereotyped spatial and temporal ordering of ZGA in a model vertebrate embryo. Unknown, however, was whether this precise ZGA patterning was required for development. To address this fundamental question, we devised a strategy to spatially control cell divisions in the embryo that perturb blastula embryo organization. We demonstrate the feasibility of spatially inverting the cell size pattern of embryos and find that these inverted embryos undergo a flipped pattern of ZGA. Mispatterned ZGA along the animal-vegetal axis causes embryo apoptosis, revealing that gastrula embryos have a built-in quality control system to sense inappropriate ZGA patterning, including regional defects in transcriptional onset. The quality control response is non-autonomous which may depend on anti-apoptotic signals that repress cell death outside of the animal hemisphere. These results reveal the requirement of properly patterned ZGA for normal development and the existence of an embryo quality control response exquisitely tuned to the spatial and temporal ordering of genome activation and zygotic gene expression.

Journal Article↗
PubMed2025

Microbiology Galaxy Lab: The first community-driven gateway for reproducible and FAIR analysis of microbial data.

The explosion of microbial omics data has outpaced the ability of many researchers to analyze it, with complex tools and limited computational resources creating barriers to discovery. To address this gap, we present the Microbiology Galaxy Lab: a free, globally accessible, community-supported platform that combines state-of-the-art analytical power with user-friendly accessibility. Supported by the Galaxy and global microbiology communities, this platform integrates over 315 tool suites and 115 curated workflows, enabling comprehensive metabarcoding, (meta)genomic, (meta)transcriptomic, and (meta)proteomic data analysis within a FAIR-aligned environment. It also supports research in the health and infectious disease sectors, as well as in environmental microbiology. The platform's utility is exemplified through various use cases, including antimicrobial resistance tracking, biomarker prediction, microbiome classification, and functional annotation of key microbes. Built on reproducibility and community engagement, it supports creation, sharing, and updating of best-practice workflows. Over 35 tutorials and learning paths empower scientists, fostering an ecosystem that keeps resources at the forefront of microbial science. The Microbiology Galaxy Lab enables collective analysis, democratising research, thereby accelerating discovery across the global microbiology community (microbiology.usegalaxy.org, .eu, .org.au, .fr).

Journal Article↗
PubMed2025

Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia.

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

Journal Article↗
PubMed2024

Multi-omic Biomarkers Distinguish Rheumatoid Arthritis in Discordant Monozygotic Twins.

BACKGROUND: Although genetic factors have been identified in the pathogenesis of rheumatoid arthritis (RA), the concordance rate in monozygotic (MZ) twins is low, suggesting that other features contribute to disease development. Further, the relative contribution of such non-genetic elements in identical twins have not been characterized. Here, we aimed to measure differentiating host and microbial biomarkers of RA by studying MZ twins discordant for disease using a multi-omics approach. METHODS: Eight pairs of MZ twins discordant for RA (n=16) were enrolled. Gut microbiome was assessed using shotgun metagenomic sequencing. Autoantibodies, cytokines, and other plasma proteins were measured in both plasma and feces. Levels of short and medium-chain fatty acids from serum and feces were quantified using gas chromatography mass spectrometry (GC-MS). RESULTS: While overall microbiome diversity and composition did not significantly differ between twins, we observed a decrease in Blautia faecis in affected twins. Affected twins had higher concentrations of both fecal and plasma citrullinated and non-citrullinated autoantibodies, as well as significantly lower concentrations of fecal butyrate and propionate. CONCLUSION: Multi-omics biomarkers differentiate MZ twins discordant for RA. Blautia faecis, which is associated with reduced inflammatory cytokine expression, was decreased in RA twins. Similarly, short-chain fatty acids, known to have immune modulatory effects, were decreased in affected twins, suggesting further bi-directional interactions between inflammation at the gut barrier and disease state. If confirmed in other cohorts, exhaustive multi-omics approaches may improve our understanding of RA pathogenesis and potentially contribute to novel diagnostics and co-adjuvant therapies.

Journal Article↗
PubMed2025

Nuclear basket proteins Nup2 and Mlp1 drive heat shock-induced 3D genome restructuring downstream of transcriptional activation.

The nuclear pore complex (NPC), a multisubunit complex located within the nuclear envelope, regulates RNA export and the import and export of proteins. Here we address the role of the NPC in driving thermal stress-induced 3D genome repositioning of Heat Shock Responsive (HSR) genes in budding yeast. We found that two nuclear basket proteins, Nup2 and Mlp1, although dispensable for NPC integrity, are required for driving HSR genes into coalesced chromatin clusters, consistent with their strong, heat shock-dependent recruitment to HSR gene regulatory and coding regions. HSR gene clustering occurs predominantly within the nucleoplasm and is independent of the essential scaffold-associated proteins Nup1 and Nup145. Notably, acute double depletion of Nup2 and Mlp1 has little effect on the formation of Heat Shock Factor 1 (Hsf1)-containing transcriptional condensates, Hsf1 and Pol II recruitment to HSR genes, or HSR mRNA abundance. Our results define a 3D genome restructuring role for nuclear basket proteins extrinsic to the NPC and downstream of HSR gene activation.

3D genome architecture↗