Biology subjects

Ali, A.

Publications and source records attributed to Ali, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Shoot to root transport of the HY5 transcription factor drives root developmental plasticity under neighbour shade.

Plants perceive competitors through the reflection of Far-Red light from neighbouring leaves. A decrease in the Red: Far-red light ratio (R:FR) is perceived by phytochrome photoreceptors and triggers elongation responses aboveground, allowing plants to anticipate future competition for light; their primary energy source. However, low R:FR perception by the shoot also prompts an alteration of root development, possibly to conserve resources. An important regulator of this response is the bZIP transcription factor ELONGATED HYPOCOTYL 5 (HY5), which can be transported from the shoot to the root, where it suppresses auxin signaling and lateral root outgrowth. However, it remains unknown whether HY5 transport is the direct link between shoot-perceived low R:FR and a decrease in lateral root outgrowth. We therefore sought to uncover the mechanics and speed of HY5 transport. To this end, we constructed shoot-specific inducible lines to perform live-imaging of HY5 transport using a vertical confocal microscope. This allowed us to follow the transport and unloading of HY5 from the phloem into the protophloem pericycle, where it becomes nuclearly localized, in real time over a 24-hour period. To mimic plant competition, we applied supplemental FR light and observed that this increased the HY5 protein levels in the shoot and subsequent HY5 protein transport from shoot-to-root. Finally, we were able to show that shoot-expressed HY5 is necessary and sufficient to induce the root response to shoot perceived Far-Red light. This work showcases in detail how a small general transcription factor functions as a long-distance signal between shoot and root and integrates environmental signalling over long distances in the plant.

plant biology↗

bioRxiv2026

Spatial epigenomics reveals ancestry-associated regulatory states linked to aggressive prostate cancer biology

Prostate cancer (PCa) exhibits substantial biological heterogeneity, including population associated differences in tumor aggressiveness and clinical outcomes. Although socioeconomic and environmental factors contribute to these disparities, intrinsic tumor regulatory programs may also influence disease behavior. Here, we investigated whether differences in chromatin regulation contribute to distinct tumor states in Black and White men with localized PCa. We performed spatial chromatin accessibility profiling (ATAC-seq) of prostatectomy specimens from Black and White patients receiving equal healthcare access at the Center for Prostate Disease Research (USUHS) and Walter Reed National Military Medical Center. Tumors showed distinct chromatin accessibility landscapes between the two populations, with tumors from Black patients exhibiting reduced accessibility of motifs associated with the chromatin architectural regulator CTCF and enrichment of motifs linked to epithelial-mesenchymal transition and inflammatory programs. Reduced CTCF expression was independently validated by immunohistochemistry in 99 prostatectomy specimens. These findings identify population-associated differences in chromatin regulation in localized PCa and suggest that altered CTCF-associated regulation, inflammatory signaling, and epithelial plasticity may contribute to the biological heterogeneity underlying ancestry-dependent PCa disparities.

cancer biology↗

bioRxiv2026

A Dynamics-Informed Machine Learning Framework for Inhibitor Optimization Against Quickly Evolving Targets to Avoid Resistance

Drug resistance often emerges through mutations that reshape protein conformational ensembles, allowing inhibitor potency to be altered without directly disrupting protein-ligand contacts. Consequently, the molecular mechanisms underlying these effects remain difficult to identify, hindering the design of inhibitors with durable potency against rapidly evolving drug targets. To address this challenge, we developed ROBUST, a physics-informed machine learning framework that integrates experimental measurements, molecular dynamics simulations, and interpretable statistical modeling to identify energetic determinants of inhibitor potency. Using HIV-1 protease as a stringent model system for drug resistance, we determined 157 new inhibition constants and integrated them with prior measurements to establish a comprehensive experimental dataset of 364 protease-inhibitor pairs. Analysis of the corresponding molecular dynamics simulations revealed a compact network of energetic interactions that quantitatively explains how resistance mutations and inhibitor modifications jointly reshape molecular recognition and inhibitor potency across the multidimensional resistance landscape. Models constructed from these energetic signatures predicted binding free energies with high accuracy (RMSE < 1 kcal mol-1) and successfully generalized to unseen darunavir analogs. Importantly, ROBUST accurately prioritized unseen analogs based on their potency across the variant set, demonstrating its utility for identifying compounds with improved resistance profiles. Together, these results uncover the energetic principles through which resistance mutations and inhibitor modifications alter potency and establish ROBUST as a mechanistically interpretable framework for translating these insights into resistance-aware inhibitor optimization against rapidly evolving drug targets.

biophysics↗

bioRxiv2026

Physiological folate levels constrain nucleotide synthesis and increase dependence on nucleotide salvage

Proliferating cells must acquire nucleotides to support DNA replication, yet how cells meet these nucleotide demands for proliferation under physiological conditions remains understudied. Here, we investigated how physiological nutrient availability shapes nucleotide acquisition strategies in a mouse model of B-cell acute lymphoblastic leukemia (B-ALL). To assess how environmental nutrients impact nucleotide metabolism, we formulated a mouse plasma-like medium (MPM) that reproduces the circulating metabolite composition of plasma from mice with B-ALL and assessed how this influenced nucleotide metabolism relative to standard culture conditions, where nucleotide acquisition has historically been studied. We find that leukemia cells cultured in MPM acquire nucleotides through salvage pathways, and that select nucleotide salvage pathways are required for proliferation under physiological conditions. Of note, this dependency on nucleotide salvage in plasma-like conditions was not caused by precursor metabolite limitation for de novo synthesis. Instead, we found that physiological folate levels are insufficient to support deoxynucleotide triphosphate (dNTP) synthesis for genome replication, leading to DNA replication stress and impaired proliferation when nucleotide salvage is disrupted. Consistently, dietary folate restriction exacerbates the impaired leukemia progression phenotype of nucleotide salvage-deficient B-ALL cells. Together, these findings demonstrate that access to folates is an endogenous limitation for nucleotide synthesis in plasma-like nutrient conditions, increasing the relevance of nucleotide salvage pathways for leukemia progression. More broadly, this work highlights how micronutrient abundance can influence metabolic dependencies and reveals that folate levels shape nucleotide metabolism under physiological conditions.

cancer biology↗

bioRxiv2026

Biomarker Fidelity Score - A Quantitative Framework for Individual-Level Validation of Explainability Methods in 3D Alzheimer's Disease MRI Classification

Explainability methods applied to deep learning models for Alzheimer's disease neuroimaging produce attribution maps that vary substantially across methods and architectures, yet no validated quantitative framework exists for determining which method most faithfully localises attribution signal within established AD biomarker anatomy at the individual subject level. Existing validation approaches rely on group-level comparisons or qualitative visual inspection, leaving individual-level biomarker alignment uncharacterised. We introduce the Biomarker Fidelity Score (BFS), a quantitative tool measuring spatial overlap between individual-level 3D explainability attention maps and atlas-registered AD-relevant neuroimaging ROIs across thirteen anatomically defined structures including hippocampus, entorhinal cortex, amygdala, and parahippocampal gyrus. Five explainability methods (GradCAM++, Integrated Gradients, DeepSHAP, LRP, ScoreCAM) were benchmarked across three volumetric architectures (3D ResNet-18, DenseNet-121, Swin-UNETR) on 327 balanced ADNI-3 subjects. Integrated Gradients achieved the highest BFS across all architectures while GradCAM++ consistently showed the lowest biomarker alignment (all p<0.001, Friedman test). The complete BFS pipeline replicated these rankings without retraining on 207 independent OASIS-3 subjects, with maximum absolute difference of 0.0005 across all fifteen method-architecture combinations and Spearman rank correlation of 0.964 between cohort rankings. By offering an externally validated, individual-level, biomarker-grounded quantitative standard, BFS equips clinicians and AI developers with practical guidance for selecting trustworthy explainability methods in AD neuroimaging.

neuroscience↗

bioRxiv2026

Ancient human mitochondrial genomes encode antimicrobial peptides

Mitochondria are bacteria-derived organelles that coordinate major innate immune pathways, but whether mitochondrial genomes themselves encode direct antimicrobial functions is underexplored. Here, we test the hypothesis that ancient human mitochondrial DNA is not only an evolutionary record, but also contains encrypted peptide sequences with the capacity to contribute to host defense. Because mitochondria descend from a bacterial endosymbiont and retain bacterial-like molecular features, we reasoned that their compact genomes might preserve sequence fragments capable of engaging bacterial-like membranes or bacterial physiology. We mined 2,025 ancient human mitochondrial genomes using a computational pipeline that couples ORF extraction and deep learning, identifying 65 candidate peptides that we term mitochondrins. We synthesized 38 candidates and experimentally validated 14 as antimicrobials against clinically relevant Gram-negative and Gram-positive bacteria. Active mitochondrins were not defined by length, charge, or helicity alone; instead, potency depended on precise hydrophobic-cationic patterning, with nested peptide families revealing how single motif-level changes can switch activity on or off. Mechanistic assays showed that mitochondrins span multiple antibacterial modalities, from strong membrane disruption to potent activity with limited membrane perturbation, suggesting noncanonical or multi-step killing mechanisms. Several peptides displayed low cytotoxicity toward human cells, and one representative mitochondrin reduced bacterial burden in a murine skin abscess model. These findings provide a biochemical basis for the hypothesis that mitochondrial genomes may contribute to innate immunity.

bioengineering↗

bioRxiv2026

Chaperone condensates buffer the heat shock response against pleiotropic inputs

Stress response pathways can be specific, dedicated to one stimulus, or pleiotropic, funneling distinct perturbations into a shared program. The heat shock response (HSR), the Hsf1-driven transcriptional program, has been linked to numerous stresses, suggesting it is pleiotropic. Here we find that high amplitude HSR activation is specific to heat shock in budding yeast. Heat shock activates the HSR through a condensate cascade in which orphan ribosomal proteins condense with Sis1 and Hsp70, titrating these chaperones away from their repressive interactions with Hsf1, triggering Hsf1 condensation with the transcriptional machinery, and activating HSR genes. Other stressors likewise drive Sis1 and Hsp70 condensation, redeploying Sis1 to stimulus-specific subcellular sites. However, chaperone condensation is not sufficient to activate the HSR. Sis1 and Hsp70 condense under conditions in which the HSR remains inactive, and Sis1 depletion increases HSR activation under all conditions except heat shock. These results suggest that chaperone condensates buffer the HSR, setting a threshold for activation and imparting specificity.

cell biology↗

bioRxiv2026

A Nerve-Dependent NGF Receptor Switch Controls Corneal Epithelial Renewal In Neurotrophic Keratopathy

Corneal epithelial integrity depends on continuous epithelial renewal by limbal epithelial stem cells (LESCs), a process tightly linked to sensory innervation. Loss or impairment of innervation causes neurotrophic keratopathy (NK), a sight-threatening degenerative disease for which rhNGF, the only FDA-approved pharmacologic therapy, often has limited efficacy in advanced or refractory disease. The mechanistic basis for this limited response remains unclear. Using surgical, genetic, and pharmacologic approaches in a rodent model of NK with corneal Schwann cell ablation or structural and functional denervation, together with primary human LESCs, we examined how denervation alters NGF receptor signaling during epithelial repair. In innervated corneas, NGF promoted epithelial regeneration through TrkA. Denervation, however, increased expression of a second NGF receptor, anti-regenerative p75NTR, and activation of its effector JNK, and reduced the activity of the TrkA effector AKT in LESCs. In this altered receptor context, denervation-induced elevation of endogenous NGF amplified p75NTR signaling, thereby explaining the failure of topical rhNGF to rescue severely denervated NK phenotype corneas. Conversely, selective TrkA activation, either with the clinical-stage agonist tavilermide, or pharmacologic or genetic inhibition/ablation of p75NTR, restored AKT signaling and rescued epithelial healing in denervated corneas independent of reinnervation. These findings identify a nerve-dependent NGF receptor switch as a key regulator of corneal epithelial renewal and establish receptor-selective modulation as a mechanistically rational therapeutic strategy for treating NK. One Sentence SummaryCorneal denervation shifts limbal epithelial stem cell signaling from pro-regenerative TrkA-AKT toward anti-regenerative p75NTR-JNK, explaining the limited efficacy of recombinant human nerve growth factor (rhNGF; cenegermin), the only approved pharmacologic therapy for neurotrophic keratopathy, in severely denervated corneas and identifying receptor-selective modulation as a mechanistically distinct therapeutic strategy.

cell biology↗

bioRxiv2026

Stage-Specific Regulation of DNA Damage Repair by the Circadian Regulator, CRY1, in Prostate Cancer

Circadian dysregulation is increasingly linked to prostate cancer (PCa) progression, yet its role in directing DNA damage response (DDR) pathway selection remains poorly understood. Here, we identify circadian cryptochrome 1 (CRY1), a core circadian regulator, as a stage-specific determinant of DDR dependencies. Integrated transcriptomic and CRISPR-based analyses reveal that CRY1 promotes non-homologous end joining (NHEJ) and base excision repair (BER)-associated programs in hormone-sensitive disease (HTS), while driving a switch toward homologous recombination (HR) dependency in castration-resistant prostate cancer (CRPC). Mechanistically, CRY1 couples proliferative signaling to genome maintenance, enabling tumor cells to tolerate genotoxic stress and sustain progression. Notably, loss of CRY1 exposes distinct, context-dependent DDR vulnerabilities, revealing repair plasticity as a targetable actionable feature of disease evolution. These findings position CRY1 as a central regulator of DDR rewiring and support CRY1-directed combination strategies with DDR inhibitors as a rationale to delay or prevent progression to advanced, treatment-resistant PCa.

cancer biology↗

bioRxiv2026

De novo protein discovery in non-model organisms

We developed plant (Parallel Annotation of Transcriptomes), a de novo method that can potentially compare RNA-seq data of any two species without a reference genome. plant is conceptually similar to chromatography. In the same way a complex mixture is filtered to isolate its individual components, we applied a computational method to identify, annotate, and quantify components across transcriptomes. The comparison points are universal protein domain annotations rather than species-specific genes, as would be the case for a differential gene expression analysis. We looked at several Selaginella species via the 1000 Plant transcriptomes initiative (1KP) where RNA-seq data for various plant species have been made publicly available. The raw reads were assembled via Trinity. The assembled transcripts were then searched against the Pfam protein domain database via InterProScan. The assembled transcripts were also quantified via kallisto. By merging these two aspects, we were able to see how often a particular protein domain - a predicted protein structure - is expressed. These quantified annotations of protein domains are comparable across species, assuming a relatively short evolutionary distance. We were also able to identify the presence of species-specific protein domains and trace each annotation back to the gene. A bubble plot was created to visualize the distributions of Pfam annotations across species as well as GO terms.

bioinformatics↗

bioRxiv2026

A method to synthesize analytical rhodoquinone standards for quantitative analysis in tissue specimen

Rhodoquinone (RQ) is a recently discovered component of the mammalian electron transport chain (ETC) with a high degree of tissue-specificity. Currently, a lack of pure analytical standards limits efforts to precisely quantify its levels using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and interrogate its biochemical functions within mammalian ETC complexes. Here, rhodoquinone-9 (RQ-9) and rhodoquinone-10 (RQ-10), and their isomeric by-products isorhodoquinone-9 (isoRQ-9) and isorhodoquinone-10 (isoRQ-10), were synthesized from ubiquinone-9 and ubiquinone-10 starting materials. Isomers were separated and purified by flash chromatography and structurally confirmed with nuclear magnetic resonance (NMR) spectroscopy. The chromatographic and fragmentation patterns of both the oxidized and reduced forms of these electron carriers were further characterized by LC-MS/MS, establishing signatures for their confident identification in lipidomics studies. LC-MS/MS analysis of murine kidney tissue with RQ-9 analytical standard spike-in corroborate the identity of the endogenous murine RQ-9 and enable absolute quantification of its levels. Thus, we synthesized and purified RQ-9 and RQ-10 analytical standards that will enable absolute quantification in mammalian tissues and in vitro reconstitution studies on RQ-9 and RQ-10 in the mammalian ETC.

biochemistry↗

bioRxiv2026

Phytochemical profiling, antioxidant capacity, and in vivo safety assessment of Warrigal spinach (Tetragonia tetragonioides) and Kensington Pride mango (Mangifera indica) extracts using Zebrafish larvae

Plant-derived bioactive compounds are recognised for their antioxidant potential and benefit for human diseases, including age-related diseases caused by oxidative stress. However, their antioxidant composition and safety profiles remain insufficiently understood. This study integrates phytochemical profiling, antioxidant evaluation, and in vivo toxicological assessment of Warrigal spinach (Tetragonia tetragonioides) and Kensington Pride mango (Mangifera indica). Spinach exhibited greater antioxidant capacity, and higher total phenolic and flavonoid content than mango: TPC (14.2 {+/-} 0.6 mg GAE/g vs 1.30 {+/-} 0.07 mg GAE/g) and TFC (9.61 {+/-} 0.39 mg QE/g vs 0.08 {+/-} 0.0 mg QE/g). LC-ESI-QTOF-MS/MS identified 187 metabolites dominated by flavonoids (53.5%) and phenolic acids (16%), with spinach showing greater chemical diversity. Quantitative analysis revealed higher levels of hydroxycinnamic acids and flavonoid glycosides in spinach, whereas mango contained distinct metabolites, including mangiferin and pyrogallol. Zebrafish embryo / larval assays demonstrated high safety margins, with LC50 values of 478.8 mg/L (spinach) and >480 mg/L (mango). At 480 mg/L spinach displayed developmental abnormalities and malformations. These findings demonstrate that antioxidant capacity is linked to phenolic composition, but does not predict toxicity. Thus, integrated phytochemical and safety evaluation for extracts with complex compound mixtures are critical to identify botanicals suitable for future drug development. HighlightsO_LIWarrigal spinach exhibited >10-fold higher phenolic content and antioxidant capacity than Kensington Pride mango. C_LIO_LILC-ESI-QTOF-MS/MS identified 187 metabolites, with flavonoids as the dominant phytochemical class. C_LIO_LIZebrafish assays confirmed high safety margins, demonstrating no direct correlation between antioxidant capacity and toxicity. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/720960v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@f82bbeorg.highwire.dtl.DTLVardef@ffd6d4org.highwire.dtl.DTLVardef@711481org.highwire.dtl.DTLVardef@1f94d7d_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

pharmacology and toxicology↗

bioRxiv2026

Continual Learning for Emerging Epitope Landscapes in TCR peptide Binding Prediction

The TCR-peptide binding landscape evolves continuously: novel pathogens (SARS-CoV-2, emerging influenza variants) and newly characterized tumor neoantigens introduce epitope families with no training precedent. Deploying a static model trained on historical data leads to degraded performance on emerging epitopes, while naive fine-tuning on new data causes catastrophic forgetting--erasing performance on previously learned epitopes. We introduce ContinualTCR, a continual learning framework that combines reservoir replay with Elastic Weight Consolidation (EWC) regularization to balance stability (retaining old-epitope performance) and plasticity (adapting to new epitopes). Evaluated on a temporally partitioned VDJdb- IEDB benchmark across four sequential epitope arrival tasks, ContinualTCR achieves new-epitope AUROC 0.812 and old-epitope AUROC 0.781 simultaneously--reducing catastrophic forgetting by 62.9% relative to naive fine-tuning. A streaming evaluation protocol with per-task backward transfer (BWT) reporting reveals that replay alone resolves 30.6% of forgetting, EWC alone resolves 57.3%, and their combination achieves synergistic complementarity. These results establish continual learning as a necessary component of production TCR specificity systems that must adapt to evolving pathogen and neoantigen landscapes without requiring full retraining.

bioinformatics↗

bioRxiv2026

Coordinated Membrane Deformation Driven by a Minimal Set of Spiroplasma MreB Isoforms

Spiroplasma are wall-less helical bacteria that swim by switching the handedness of their helices. In most bacteria, MreB, a bacterial actin, forms relatively static filaments beneath the membrane to organize cell wall synthesis. In contrast, Spiroplasma eriocheiris encodes five MreB isoforms (SpeMreBs), and swimming requires a pair of isoforms, SpeMreB5 together with SpeMreB4 (or the related isoform SpeMreB1) (1) Yet how these MreBs generate force and membrane deformation remains unclear. To examine the membrane-deforming activities of SpeMreBs, we demonstrated a simple reconstitution system using the non-motile synthetic bacterium JCVI-syn3B and purified SpeMreBs expressed in Escherichia coli. Lysates of syn3B expressing SpeMreB5 deformed liposomes in a concentration-dependent manner. In contrast, lysates co-expressing both SpeMreB5 and SpeMreB4 showed a plateau in the frequency of deformation, suggesting that SpeMreB4 suppresses membrane deformation driven by SpeMreB5. Deformed liposomes exhibited either fluctuating or stable behaviors. ATP depletion changed both the frequency and behavior of deformation, indicating that membrane remodeling depends on the nucleotide state of SpeMreBs. Reconstitution with purified SpeMreBs from E. coli confirmed that SpeMreB5 alone deforms membranes, whereas SpeMreB1, a member of the same class as SpeMreB4, suppresses deformation. These results suggest that membrane shape in Spiroplasma is dynamically regulated by antagonistic interactions among isoforms of SpeMreBs isoforms and their nucleotide-dependent assembly states.

synthetic biology↗

bioRxiv2026

Physiological architecture and evolutionary origins of cellular adaptability

The capacity to adapt to complex environments ( adaptability) is a defining property of cells. Yet, its relationship across single-cell physiology, population-level responses, and evolutionary timescales remains unclear. We performed single-cell transcriptional profiling of budding yeast across 20 complex environments before and after long-term selection for increased osmotolerance. In ancestral populations, transcriptional responses organized into a reproducible hierarchy where adaptation to certain cues took precedence over others. This hierarchy mechanistically originated within individual cells through contingent regulation of translation initiation. Evolution for >3,000 generations under osmotic stress increased osmotolerance while reordering this hierarchy, selectively deprioritizing osmotic stress as an organizing axis of adaptation. The derived strain exhibited impaired integration of stress responses, defective translational coordination, and reduced fitness outside the selected condition. Together, these findings illustrate that cellular adaptability is an evolved architecture whose form is set by the history of selection. One Sentence SummaryCells adapt to complex environments via a prioritization hierarchy; this hierarchy is shaped by the frequency and magnitude of environmental fluctuations in their evolutionary history.

cell biology↗

bioRxiv2026

Lineage-Specific Venom Gene Expression Shapes Chemical Diversity in Cephalopods

Animal venoms represent a major source of chemical novelty, yet how venom compounds originate, diversify, and are maintained across deep evolutionary timescales remains poorly understood. This gap is especially pronounced in cephalopods, which evolved venom systems used in predation, defense, and sexual competition, but whose venom genetic architectures, secretory cell types, and venom-producing glands remain largely unexplored. To date, only a single cephalopod venom compound with confirmed paralytic activity and a known primary sequence, SE-CTX from the golden cuttlefish Acanthosepion esculentum, has been described. Here, we reconstruct the evolutionary history, molecular diversity, and glandular localization of SE-CTX-like proteins using a multimodal approach. We identify 29 homologs across 20 squid and cuttlefish species and define a previously unrecognized venom gene family, which we name deca-ctx, specific to decapodiform cephalopods (squids and cuttlefish). Phylogenetic analyses reveal a single origin of deca-ctx followed by gene duplication and lineage-specific diversification, indicating long-term retention of this venom gene. Predicted DECA-CTX protein structures were separated into two clusters and 20 singletons highlighting potentially extensive structural diversity within a single cephalopod venom gene family. Proteomic analysis confirms expression of five DECA-CTX proteins across three species. Our imaging and histological analyses localize deca-ctx expression to specialized secretory cells within squid and cuttlefish venom glands. Together, these findings reposition SE-CTX as part of an evolutionarily and chemically diverse venom system, rather than an isolated venom protein, and establish cephalopods as a key lineage for investigating how new venom genes arise, diversify, and are integrated into functional venom arsenals.

evolutionary biology↗

bioRxiv2026

Exploring transcriptomic and genomic latent variable correction approaches in differential expression analysis.

BackgroundDifferential expression analysis is a central tool for studying the biological processes altered in human diseases via transcriptomic signatures. However, transcriptomic datasets are systematically confounded by latent variables from two distinct sources: unmeasured technical and biological heterogeneity within the expression data, and expression differences driven by population stratification. Correction using expression-based surrogate variables (SVs) and genotype-based principal components (PCs) addresses these sources independently, yet no study has directly evaluated their combined use against either method alone within a differential expression framework. In this study we hypothesised that simultaneously including both correction layers would produce more biologically valid and reproducible results than either approach alone, and tested this in two independent RNA-seq datasets of amyotrophic lateral sclerosis (ALS) cases and controls with matching genotype data. ResultsFour nested differential expression models (corrected for PC-only, SV-only, both SV and PC, and neither PCs nor SVs) were evaluated across the KCLBB (96 cases and 52 controls) and ALS Consortium (272 cases and 35 controls) datasets. Models were evaluated on: cross-dataset effect size concordance, cross-dataset replicability quantified by the Jaccard Similarity Index, and biological recall against a curated reference set of 66 known ALS genes. The combined SV+PC framework consistently outperformed simpler models across all metrics. Replicability improved nearly ten-fold compared to the non-corrected model, (Jaccard index: 2.28% to 19.5%), and the combined framework exhibited a statistically significant 2.1% gain over the SV-only model. The biological recall ALS genes recovered doubled comparing to the SV correction alone. Crucially, effect size stability was preserved, with the combined model expanding the shared transcriptomic signal without sacrificing consistency. These findings remained generally robust to PC number in sensitivity analyses. ConclusionsThis study found that SVs and genotype PCs address non-redundant sources of confounding, and we recommend their combined use as standard practice in differential expression analysis where matched genotype data are available. Notably PCs capturing population structure can also be derived directly from RNA-seq data, extending the applicability of this framework to studies lacking matched genotype data. Although this analysis was restricted to ALS datasets, we expect these findings to generalise to other traits.

bioinformatics↗

bioRxiv2026

EGP1K: Whole-Genome Sequencing of 1,024 Egyptians Characterizes Population Structure and Genetic Diversity

Middle Eastern and North African populations remain underrepresented in genomic databases, comprising less than 1% of genome-wide association study participants despite representing approximately 6% of the global population. Here we present the Egypt Genome Project (EGP1K), in which we performed whole-genome sequencing on 1,024 unrelated Egyptian individuals originating from 21 of Egypts 27 governorates, recruited through eight clinical and research centers across Upper and Lower Egypt. We identified over 51.3 million variants, of which 17.1 million (33.4%) were absent from dbSNP. Allele frequency comparisons across 6.5 million shared variants showed the strongest concordance with Middle Eastern populations ({tau} = 0.977). Principal component analysis and ADMIXTURE modeling at K = 7 revealed that Egyptians share a dominant ancestry component (71.8%) with Middle Eastern populations and carry a smaller Egyptian-enriched component (18.5%) that distinguishes them from neighboring groups. Runs of homozygosity varied substantially across subregions, with Upper Egypt showing the highest burden, paralleling elevated consanguinity rates. Carrier frequency analysis identified MEFV (Familial Mediterranean Fever) at 9.1% as the most prevalent pathogenic carrier state; when adjusted for the national consanguinity rate, MEFV carrier status alone projects approximately 6,600 affected births per year. HLA class I typing identified allele frequencies placing Egyptians within the Levantine-Eastern Mediterranean cluster, providing baseline immunogenetic data currently absent from international databases. Analysis of polygenic risk score distributions revealed substantial differences in threshold-based risk stratification between Egyptians and European reference populations. When the Europeanderived 90th percentile threshold was applied, 83.3% of Egyptians were assigned to high-risk strata for stroke, 76.4% for chronic kidney disease, and 72.8% for gout, compared to the intended 10% high-risk proportion. These distributional shifts were observed across several cardiometabolic traits (Cohens d = 1.55-1.61), while other traits showed closer cross-population concordance, indicating that the degree of threshold miscalibration varies by trait. Together, these findings establish EGP1K as a genomic reference for Egypt and indicate that European-derived risk stratification thresholds may not be directly transferable to the Egyptian population, supporting the need for population-specific calibration of polygenic risk scores.

genomics↗