Biology subjects

Farooq, H.

Publications and source records attributed to Farooq, H..

18 recordsLinked to original sources

bioRxiv2026

Disentangling polymer confinement from specific-folding interactions reveals the drivers of E. coli chromosome organization

The three-dimensional organization of the bacterial chromosome is critical for gene regulation. Chromosome conformation capture (Hi-C) has enabled genome-wide mapping of chromosomal folding, yet ensemble-averaged contact maps entangle biologically specific-folding interactions (SFIs) with nonspecific polymer compaction and mask single-cell heterogeneity. Here, we developed a polymer-based simulation framework in E. coli to address these limitations. We found that a null model of 300,000 random polymer configurations recapitulated the global chromosomal organization observed in Hi-C data, establishing that most Hi-C signals reflect generic polymer behavior in a confined volume. Contrasting null-model predictions with experimental Hi-C data isolated a small subset of SFIs (< 7%) and generated a specific-fold ensemble of 20,000 single-cell conformations that reproduced chromosomal interaction domains and single-cell heterogeneity. SFIs were enriched in the ter region, reduced nucleoid accessibility, colocalized with cryptic prophages, and depleted in positively supercoiled regions. H-NS and MatP emerged as major chromosome-wide and local determinants of SFIs, respectively. Furthermore, high-SFI regions correlated with stress-adaptive genes, whereas low-SFI regions harbored housekeeping genes. Together, our results established that a small number of biologically encoded SFIs superimposed on a polymer background shape the E. coli chromosome and gene expression, providing a quantitative framework for dissecting chromosome architecture and function.

genomics↗

bioRxiv2026

Global vertebrate hotspots

Effective biodiversity conservation requires tools that can identify priority areas under growing human pressures. Building on the concept of global biodiversity hotspots, we present a transparent and repeatable approach to mapping conservation priorities using data for 33,604 species of terrestrial vertebrates from the IUCN Red List. This framework expands the taxonomic scope of previous efforts and integrates updated information on key human-driven threats to biodiversity. We identify that around 13% of Earths terrestrial surface qualifies as vertebrate conservation hotspots, often shaped by distinct combinations of species groups and threats. These results highlight the need for tailored, context-specific conservation strategies. By providing a robust method to guide spatial prioritization, our work supports more effective implementation of conservation targets in a rapidly changing world.

ecology↗

bioRxiv2025

10.5 Tesla High-Resolution Macaque Brain MRI for Connectivity Studies

Mapping brain connectivity in primates remains a major challenge due to difficulties in resolving microscopic white matter architecture, while maintaining whole-brain coverage. Increasing imaging spatial resolution is key for disambiguating fibre configurations within smaller anatomical volumes. Here, we present novel developments that allow high-resolution diffusion MRI of the macaque brain using one of the world's highest-field human MRI scanners operating at 10.5 Tesla, allowing both in vivo and ex vivo macaque brain imaging. Our approach achieves very high spatial resolution across both tissue states, (up to 580 m)3 in vivo and (300 m)3 ex vivo, with diffusion weighting up to b = 6000 s/mm2. We detail methodological advances in data acquisition, image reconstruction, processing and whole-brain tractography that overcome critical challenges associated with ultra-high-field imaging. This work establishes a new framework for high-resolution in vivo and ex vivo neuroimaging of the NHP brain at 10.5 T using a human bore scanner, paving the way for subsequent analyses of brain connectivity across species and tissue states at unprecedented detail. The dataset, along with all processing pipelines, containerised workflows, and reusable web services, is openly shared to support reproducibility and future integration with microscopy for studying white matter microstructure and connections at the mesoscale.

neuroscience↗

bioRxiv2025

Diffusion-weighted steady-state free precession imaging in the ex vivo macaque brain on a 10.5T human MRI scanner

Diffusion MRI provides a non-invasive probe of local fibre bundles and long-range anatomical connections to characterise the structural connectome. One way to achieve very high spatial resolution diffusion MRI data for connectivity investigations is to scan ex-vivo brains over many hours or days, ideally at ultra-high field strength to boost signal levels. However, conventional diffusion MRI acquisition techniques do not generally deliver good data quality for the challenging conditions of ex-vivo tissue, characterised by reduced diffusivities and relaxation times when compared to in vivo. In this work, we investigate the potential of the diffusion-weighted steady-state free precession (DW-SSFP) sequence for ex vivo diffusion imaging of the macaque brain using a 10.5 T human MRI scanner with a conventional (Gmax = 70 mT/m) gradient set. SNR-efficiency optimisations incorporating experimental relaxation times demonstrate that the DW-SSFP sequence is predicted to achieve improved or similar SNR efficiency compared to a diffusion-weighted spin- and stimulated-echo sequence. Importantly, DW-SSFP can achieve this with the additional benefit of negligible geometric distortions, unlike conventional diffusion MRI using an echo-planar imaging readout. Using optimised DW-SSFP sequence parameters, we propose a protocol at 0.4 mm isotropic resolution using a two-shell multi-orientation protocol (effective b-values of 3200 s/mm2 and 5600 s/mm2). We fit the data using Tensor, Ball and 3-Sticks and Constrained Spherical Deconvolution signal representations. The results demonstrate high-quality diffusivity estimates across the entire brain with the ability to resolve multiple fibre populations in challenging crossing-fibre regions. The data will be made fully open source and multimodal as part of the Center for Mesoscale Connectomics, providing a resource for future connectivity investigations.

neuroscience↗

bioRxiv2025

ChromPolymerDB: A High-Resolution Database of Single-Cell 3D Chromatin Structures for Functional Genomics

The three-dimensional (3D) organization of chromatin plays a critical role in regulating gene expression and genomic processes like DNA replication, repair, and genome stability. Although these processes occur at the individual-cell level, most chromatin structure data are derived from population-averaged assays, such as Hi-C, obscuring the heterogeneity of single-cell conformations. To address this limitation, we developed a polymer physics-based modelling framework, the Sequential Bayesian Inference Framework (sBIF), that deconvolutes bulk Hi-C data to reconstruct single-cell 3D chromatin conformations. To support a broader use of sBIF, we created ChromPolymerDB, a publicly accessible, high-resolution database of single-cell chromatin structures inferred by sBIF. The database contains [~]108 reconstructed 5 kb-resolution single cell structures, spanning over 60,000 genomic loci across 50 human cell types and experimental conditions. ChromPolymerDB features an interactive web interface with tools for 3D structural analysis and multi-omics integration. Users can explore associations between chromatin conformation and gene expression, epigenetic modifications, and regulatory elements. The platform also supports comparative analyses to identify structural changes across cell types, developmental stages, or disease contexts. ChromPolymerDB offers a unique resource for researchers studying the relationship between genome architecture and gene regulation, and for advancing comparative 3D genomics. ChromPolymerDB is available online at https://chrompolymerdb.bme.uic.edu/. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/678816v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@110c807org.highwire.dtl.DTLVardef@bc713forg.highwire.dtl.DTLVardef@1af0ea9org.highwire.dtl.DTLVardef@1eba638_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Leaf shape modulates climate trait relationships in the wild species Chenopodium hircinum (Amaranthaceae)

Understanding how leaf morphology mediates plant responses to environmental variation is essential for predicting species adaptability under climate change. In this study, we investigated natural variation in leaf shape and associated functional- physiological traits (FPTs) across populations of Chenopodium hircinum grown in a common garden. We found that leaf shape strongly correlates with the climatic conditions of population provenance, while functional and physiological traits are independently associated with morphology rather than directly with climate. Landmark-based morphometric analysis revealed that the second principal component, distinguishing deeply lobed from rounded leaves, is significantly linked to key traits such as leaf mass per unit area (LMA) and stomatal conductance. These relationships suggest that morphology mediates a functional continuum between resource-use strategies. Notably, within-population phenotypic variation accounted for much of the observed trait diversity, underscoring the role of individual-level phenotypic plasticity in shaping ecological function. Our results challenge traditional views on the thermoregulatory role of leaf lobation and highlight morphology as a central axis of adaptation. This work advances understanding of trait integration in response to environmental heterogeneity and suggests that plasticity in leaf shape and function may enhance resilience of C. hircinum across its native range.

plant biology↗

bioRxiv2025

Effects of Lamina-Chromatin Attachment on Super Long-Range Chromatin Interactions

The interactions between chromatin and lamin proteins localized on the nuclear envelope play a crucial role in the three-dimensional (3D) organization of the genome. This study investigates the influence of lamin associated domains (LADs) on genome organization at the chromosome level using 3D polymer models of mouse embryonic fibroblasts (MEFs) and embryonic stem cells (mESCs). By integrating genome-wide LAD maps from DamID assays, we simulated chromatin conformations with and without LAD attachment to the nuclear envelope. Our results show that incorporating LAD-lamin interactions yields a radial chromatin distribution consistent with experimental observations. Moreover, LAD-lamin interactions induce significant super long-range chromatin contacts across distant genomic regions. These findings suggest two distinct mechanisms driving induction of chromatin interactions by LAD-lamin attachment.

genomics↗

bioRxiv2024

Experimental Design Optimization for Brain Microstructure Imaging via Automatic Differentiation

Accurate characterization of the brain microstructure using diffusion MRI (dMRI) relies on optimal (i.e. information-rich) scanning protocols. Presently, without such protocols, extensive datasets are necessary to image the intricate microarchitecture of the brain by fitting complex biophysical models to the data. This impedes the full realization of dMRIs potential, particularly in time-constrained clinical scans. To tackle this, we introduce a novel framework based on the Cramer-Rao lower bound (CRLB) to optimize dMRI protocols for any multi-compartment biophysical models, to accurately capture features like axonal diameter index and multiple fiber orientations in a voxel. Unlike previous methods, limited in model complexity or parameter scope, our framework handles all model parameters, including water diffusivities, enhancing estimation fidelity. Leveraging automatic differentiation and parallel computing via TensorFlow, this approach systematically explores the entire parameter space for comprehensive scanning protocol optimization. By optimizing dMRI protocols, this work stands to significantly enhance biophysical modeling accuracy, thereby deepening our understanding of the brain microstructure in health and disease.

neuroscience↗

bioRxiv2024

Structural Basis of Differential Gene Expression at eQTLs Loci from High-Resolution Ensemble Models of 3D Single-Cell Chromatin Conformations

MotivationTechniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on the organization of the nucleus and the genome important for understanding gene expression regulation. Additionally, Genome-Wide Association Studies (GWASs) have uncovered thousands of loci related to complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs located in non-coding regions are unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. ResultIn this work, we developed a computational method for simultaneous analysis of Hi-C and eQTL data. Our method can identify a small set of non-random interactions from all Hi-C interactions. Using these non-random interactions, we reconstruct large ensemble (x105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, which accurately replicate Hi-C measurements. Our results revealed the presence of many-body interactions in chromatin conformation at single-cell level in eQTL locus, offering detailed view into how three-dimensional structures of chromatin form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression level of their associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level to reveal their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single cell chromatin conformations from Hi-C, along with eQTL data, helps to decipher how chromatin 3D structures provide the physical basis for gene regulation, expression control, and aid in understanding of the overall structure-function relationships of genome organization. Availability and implementation: It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci

bioinformatics↗

bioRxiv2024

A New Approach for Discovering Functional Links Connecting Non-Coding Regulatory Variants to Gene Targets

Genome-wide association studies (GWAS) have linked thousands of genetic variants to various complex traits or diseases. However, most identified variants have weak individual effects, are correlated with nearby polymorphisms due to linkage disequilibrium (LD), and are located in non-coding cis-regulatory elements (CREs). These characteristics complicate the assessment of the direct impact of each variant on tissue specific gene expression and phenotype. To address this challenge, we have developed a novel algorithm that leverages polymer folding and 3D chromatin interactions to prioritize and identify putative causal variants and their target genes. From the millions of eQTL-Gene pairs identified by GTEx in human somatic tissues, we classify only [~]10-20% as putative functional eQTL-Gene pairs supported by phenotypic associations confirmed through CRISPR deletion experiments. Our findings show that unlike most variants, functional eQTL-Gene pairs predominantly reside within the same topologically associating domain (TAD) and have strong associations with cell-type specific cis-regulatory elements (CREs), enriched for binding sites of tissue-specific transcription factors. Unlike most approaches that rely on linear distance or other chromatin features (histone code, accessibility), our algorithm emphasizes the importance of physical interactions and 3D chromatin folding in gene regulation, as the identified eQTL-Gene pairs are all among the small fraction of physical chromatin interactions sufficient for chromatin locus folding. Overall, our algorithm reduces false positive associations between DNA variants and genes identified by eQTL analysis and uncovers novel variant-gene pair associations. These findings suggest a mechanism where a small number of regulatory variants control tissue specific gene expression via their physical association with target genes confined within the same TAD. Our approach provides new insights into the molecular mechanisms driving GWAS phenotypes.

genomics↗

bioRxiv2024

Mapping polarization-sensitive optical coherence tomography and ultra-high-field diffusion MRI in the macaque brain

This paper provides comparisons between microstructure and two-dimensional fiber orientations measured optically using polarization sensitive optical coherence tomography (PS-OCT) and those estimated from ultra-high-field diffusion MRI (dMRI) at 10.5T in the macaque brain. The PS-OCT imaging is done at an in-plane resolution of [~]10 microns in and around the thalamus. Whole brain dMRI is acquired at an isotropic resolution of 0.75 mm. We provide comparisons between cross-polarization and optical orientation from PS-OCT with the fractional anisotropy and two-dimensional orientations extracted from dMRI using a diffusion tensor model. The orientations from PS-OCT are also extracted computationally using a structure tensor. Additionally, we demonstrate the utility of mesoscale, PS-OCT imaging in improving the MRI resolution by learning the mapping between these contrasts using a super-resolution Generative Adversarial Network.

neuroscience↗

bioRxiv2023

The threats to reptiles at global and regional scales

At least 20% of reptiles are currently threatened with extinction. Due to the lack of comprehensive global assessments of the group, they have been omitted from spatial studies, especially the ones addressing conservation or spatial prioritization. With the recent release of global assessments for reptiles, in this study, we calculate the probability of seven biodiversity threats - logging, pollution, agriculture, invasive species, hunting, climate change and urbanization occurring at a global scale on a 50x50km grid and their impact measured as the probability of finding a threatened species. Despite the global nature of our approach, we compartmented the terrestrial land into 12 regions and conducted separate analyses on each region. We find that despite globally low levels of intensity, climate change and invasive species have the highest impact on reptiles. But when looked at the regional level, various threats have a high impact on biodiversity, even surpassing climate change and invasives. Our study highlights the importance of going beyond measuring the intensity of threats to measure impact and also the importance of subdividing the world into smaller units and testing the impacts separately.

zoology↗

bioRxiv2022

Drivers of dispersal and diversification in bromeliads

O_LIDispersal strategies strongly influence an array of plant traits, especially the shape and function of fruits and seeds, and can be important drivers of diversification dynamics. In this study we investigated how fruit morphology and habitat influence dispersal capacity and diversification rate in bromeliads. We hypothesize that (1) the evolution of berry fruits increased dispersal capacity and diversification rates; and (2) climatic factors contribute to increased dispersal capacity and diversification rates. C_LIO_LITo understand the influence of fruit and habitat traits on evolutionary dynamics, we generated a time-calibrated phylogeny including 1,268 species of bromeliads and integrated that evolutionary framework with distribution, habitat, and morphological trait data. C_LIO_LIWe find that lineages with berry fruits have the highest rates of diversification. We also identify significant correlation between diversification rates and both elevation and forest canopy height. We demonstrate that dispersal capacity is not related to fruit morphology and covaries with forest canopy height and mean annual temperature. C_LIO_LIWe show that factors influencing the dispersal capacity and diversification are heterogeneous among the subfamilies. These new insights into the rise and spread of bromeliads emphasize the importance of considering the plurality of morphological and ecological features to improve the understanding of the evolutionary dynamics. C_LI

evolutionary biology↗

bioRxiv2022

In vivo functional genomics identifies essentiality of potassium homeostasis in medulloblastoma

The identification of cancer maintenance genes--driver genes essential to tumor survival--is fundamental for developing effective cancer therapy. Transposon-based insertional mutagenesis screens can identify cancer driver genes broadly but not discriminate maintenance from progression or initiation drivers, which contribute to cancer phenotypes and tumorigenesis, respectively. We engineered a nested, double-jumping transposon system to first dysregulate gene expression during tumorigenesis and then restore gene expression following tumor induction, allowing for genome-wide screening of maintenance essentiality in vivo. In a mouse model of medulloblastoma, the most common pediatric malignancy, insertion and remobilization of this nested transposon uncovers potassium channel genes as recurrent maintenance drivers. In human medulloblastoma, KCNB2 is the most overexpressed potassium channel across Group 3, Group 4, and SHH subgroups, and Kcnb2 knockout in mice diminishes the replicative potential of medulloblastoma-propagating cells to mitigate tumor growth. Kcnb2 governs potassium homeostasis to regulate plasma membrane tension-gated EGFR signaling, which drives proliferative expansion of medulloblastoma-propagating cells. Thus, our novel transposon system reveals potassium homeostasis as essential to tumor maintenance through biomechanical modulation of membrane signaling.

cancer biology↗

bioRxiv2022

A call for improving the Key Biodiversity Areas framework

Eight percent of all land surface has been designated as "Key Biodiversity Areas" (KBAs). Since these areas were established based on only two percent of all terrestrial species estimated to exist, we ask what would happen if we used all species on Earth to identify additional KBAs. We explore this question at a global scale by using data from 64,110 species of animals and plants to identify how many areas could qualify as KBAs under current criteria. We find that between 26% and 68% of the worlds terrestrial areas can be classified as KBAs, depending on the spatial resolution. The total area from potential KBAs increases drastically as more species are assessed, suggesting that if all species were included, virtually all land surface could eventually meet the biological requirements for becoming a KBA. In addition, KBAs lack a data-driven ranking system, thus assuming that all KBAs are equally worthy protection. KBAs are intended to be areas which are both of biological importance and manageable but the current approach largely sidesteps the biological component. We make an urgent call for stricter criteria in the KBA methodology or alternative methodologies that allow for biologically robust area prioritization, help secure evidence-based investments, and support progress towards the targets under the new Global Biodiversity Framework.

ecology↗

bioRxiv2020

WEGE: A NEW METRIC FOR RANKING LOCATIONS FOR BIODIVERSITY CONSERVATION

AimIn order to implement effective conservation policies, it is crucial to know how biodiversity is distributed and one of the most widely used systems is the Key Biodiversity Areas (hereafter KBA) criteria, developed by the International Union for Conservation of Nature (IUCN). Here we develop a tool to rank Key Biodiversity Areas in a continuous scale to allow the ranking between KBAs and test this tool on a simulated dataset of 10 000 scenarios of species compositions of reptiles and mammals in eight locations in Mozambique. LocationMozambique, Africa MethodsWe compare the KBA criteria with four priorisation metrics (weighted endemism, extinction risk, evolutionary distinctiveness and EDGE score) to rank the biodiversity importance of eight sites with a randomly generated species composition of reptiles and mammals in Mozambique. ResultsWe find that none of these metrics is able to provide a suitable ranking of the sites surveyed that would ultimately allow prioritization. We therefore develop and validate the "WEGE index" (Weighted Endemism including Global Endangerment index), which is an adaptation of the EDGE score (Evolutionarily Distinct and Globally Endangered) and allows the ranking of sites according to the KBA criteria but on a continuous scale. Main conclusionsFor our study system, the WEGE index scores areas that trigger KBA status higher and is able to rank their importance in terms of biodiversity by using the range and threat status of species present at the site. Prioritization may be crucial for policy making and real-life conservation, allowing the choice between otherwise equally qualified sites according to the KBA categories. WEGE is intended to support a transparent decision-making process in conservation.

ecology↗

bioRxiv2018

Childhood cerebellar tumors mirror conserved fetal transcriptional programs

The study of the origin and development of cerebellar tumours has been hampered by the complexity and heterogeneity of cerebellar cells that change over the course of development. We used single-cell transcriptomics to study >60,000 cells from the developing murine cerebellum, and show that different molecular subgroups of childhood cerebellar tumors mirror the transcription of cells from distinct, temporally restricted cerebellar lineages. Sonic Hedgehog medulloblastoma transcriptionally mirrors the granule cell hierarchy as expected, whereas Group 3 medulloblastoma resemble Nestin+ve stem cells, Group 4 medulloblastomas resemble unipolar brush cells, and PFA/PFB ependymoma and cerebellar pilocytic astrocytoma resemble the prenatal gliogenic progenitor cells. Furthermore, single-cell transcriptomics of human childhood cerebellar tumors demonstrates that many bulk tumors contain a mixed population of cells with divergent differentiation. Our data highlight cerebellar tumors as a disorder of early brain development, and provide a proximate explanation for the peak incidence of cerebellar tumors in early childhood.

cancer biology↗

bioRxiv2017

Network Curvature as a Hallmark of Brain Structural Connectivity

Studies show that while brain networks are remarkably robust to a variety of adverse events, such as injuries and lesions due to accidents or disease, they may be fragile when the disturbance takes place in specific locations. This seems to be the case for diseases in which accumulated changes in network topology dramatically affect certain sensitive areas. To this end, previous attempts have been made to quantify robustness and fragility of brain functionality in two broadly defined ways: (i) utilizing model-based techniques to predict lesion effects, and (ii) studying empirical effects from brain lesions due to injury or disease. Both directions aim at assessing functional connectivity changes resulting from structural network variations. In the present work, we follow a more geometric viewpoint that is based on a notion of curvature of networks, the so-called Ollivier-Ricci curvature. A similar approach has been used in recent studies to quantify financial market robustness as well as to differentiate biological networks corresponding to cancer cells from normal cells. The same notion of curvature, defined at the node level for brain networks obtained from MRI data, may help identify and characterize the effects of diseases on specific brain regions. In the present paper, we apply the Ollivier-Ricci curvature to brain structural networks to: i) Demonstrate its unique ability to identify robust (or fragile) brain regions in healthy subjects. We compare our results to previously published work which identified a unique set of regions (called structural core) of the human cerebral cortex. This novel characterization of brain networks, complementary to measures such as degree, strength, clustering or efficiency, may be particularly useful to detect and monitor candidate areas for targeting by surgery (e.g. deep brain stimulation) or pharmaco-therapeutic agents; ii) Illustrate the power our curvature-derived measures to track changes in brain connectivity with healthy development/aging and; iii) Detect changes in brain structural connectivity in people with Autism Spectrum Disorders (ASD) which are in agreement with previous morphometric MRI studies.

neuroscience↗