Biology subjects

Gomez, L.

Publications and source records attributed to Gomez, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Missense LMNA Variant Compromises Nuclear Integrity and Sarcomeric Remodeling in Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and cardiac transplantation, and pathogenic variants in LMNA are a well-established cause of inherited DCM. The LMNA gene encodes nuclear lamins A/C, which maintain nuclear integrity, regulate gene expression and mediate mechanotransduction. Here, we investigated the pathogenic consequences of the NM_170707.4(LMNA):c.274C>T NP_733821.1:p.(Leu92Phe) variant, previously associated with lipodystrophy features, using patient-derived induced pluripotent stem cells, differentiated into cardiomyocytes and show implication of LMNA in sarcomere remodeling and mitochondria efficiency. We generated iPSC lines from two DCM patients carrying LMNA p.Leu92Phe variant in heterozygous form and a healthy parental control. Cardiomyocytes differentiation efficiency was preserved, however, LMNAp.Leu92Phe iPSC-CMs exhibited laminopathies associated phenotypes, such as nuclear shape abnormalities and lamin A/C aggregation. Moreover, in vitro study revealed that LMNA p.Leu92Phe iPSC-CMs alter sarcomere reformation and decrease mitochondrial respiration after cardiomyocyte remodeling, which is associated with a worsening nuclear shape phenotype. Functional analyses highlight defects in calcium handling, thereby explaining arrhythmia and dilated cardiomyopathy features in patients. Our results show that the LMNA p.Leu92Phe variant compromises nuclear lamina integrity and disrupts functional cardiomyocyte properties, particularly during sarcomere remodeling, highlighting the long-term impact of this specific variant in LMNA-associated DCM.

genetics↗

bioRxiv2026

Evaluating sequence-to-function deep learning models for ancestry-stratified regulatory variant effect prediction using multi-ancestry blood eQTLs

BackgroundSequence-to-function (S2F) deep learning models are increasingly used to prioritize non-coding regulatory variants, but their behavior across ancestrally diverse populations remains unclear. Because both training data and reference resources are heavily European-centered, multi-ancestry benchmarks are needed to determine whether S2F scores capture regulatory effects consistently across populations with different allele-frequency and LD patterns. MethodsWe evaluated Borzoi and AlphaGenome using whole blood eQTL data from the MAGENTA cohort, including African American (AA; N = 224), Caribbean Hispanic (CH; N = 209), and Non-Hispanic White (NHW; N = 235) participants. Model predictions were benchmarked against sampled nominal eQTLs and ancestry-stratified SuSiE fine-mapped variants using Spearman correlation, direction concordance, inter-model convergence, and distance-matched AUROC, with sensitivity analyses for minor allele frequency and comparison-set definition. We also compared FILER functional annotation overlap among high-Posterior Inclusion Probability (PIP) variants across ancestries. ResultsBoth models showed weak agreement with nominal eQTL effect sizes across ancestries and TSS-distance bins ({rho} [≤] 0.138), with direction concordance only marginally above chance. Agreement and discrimination improved for high-confidence fine-mapped variants, and Borzoi and AlphaGenome showed stronger inter-model convergence on fine-mapped variants than on nominal eQTLs, consistent with enrichment for regulatory variants whose effects are more apparent to sequence-based models. In distance-matched AUROC analyses at PIP [≥] 0.9 using PIP < 0.01 variants as low-PIP comparison variants, the AA high-PIP variant set yielded the highest discrimination for both Borzoi (0.837 [95% CI: 0.790-0.870]) and AlphaGenome (0.820 [0.793-0.845]). The CH-versus-NHW ordering was model-dependent: Borzoi yielded higher AUROC in NHW than CH, whereas AlphaGenome produced nearly identical CH and NHW estimates. AUROC values were lower when intermediate-PIP variants were used as comparison variants, but the AA set retained the highest discrimination. MAF-stratified sensitivity analyses attenuated some ancestry contrasts but did not eliminate the higher AA discrimination pattern. Functional annotation analysis showed that AA high-PIP variants more often overlapped chromatin accessibility and chromatin-contact annotations than NHW variants, despite lower overlap with prior eQTL and sQTL annotation catalogs. ConclusionsBorzoi and AlphaGenome showed limited agreement with nominal eQTL effect sizes, but better distinguished high-confidence fine-mapped eQTLs from low-PIP variants. These results support using S2F scores as prioritization evidence for fine-mapped regulatory variants, especially promoter-proximal high-PIP variants, rather than as standalone predictors of eQTL effect size. The strongest discrimination was observed for the AA high-PIP variant set. Overall, the AA result is best interpreted as stronger separation of high-PIP variants from lower-PIP comparison variants, shaped by fine-mapping resolution, LD, the choice of comparison variants, and annotation composition.

bioinformatics↗

bioRxiv2026

SenoQuant: One-stop AI software for senescence marker analysis and prediction

Senescent cells accumulate with age and contribute to tissue dysfunction, yet their identification in tissues is challenging due to low abundance, heterogeneous phenotypes, and the lack of specific markers. Senescence-associated features span multiple subcellular compartments, including nuclear DNA damage foci, cytosolic protein changes, and perinuclear alterations, each requiring tailored detection strategies. To overcome these challenges, we developed SenoQuant (https://github.com/HaamsRee/senoquant), a versatile software designed for comprehensive, accurate, and unbiased spatial quantification and prediction of senescence markers across diverse tissue contexts. Utilizing AI models, SenoQuant enables precise nuclear and cytoplasmic segmentation and detection of senescence markers across low- and high-plex imaging modalities, applicable to cultured cells and tissue sections from mice and humans. The platform also supports custom AI models; for example, we built SenCeption, a proof-of-concept predictor of single-cell p21 status from DAPI-stained nuclei in human skin. Available as a free napari plugin, SenoQuant is widely accessible to researchers. By providing a unified approach to senescence analysis and prediction, SenoQuant opens new opportunities for exploring the complex biology of senescence and its impacts on aging and disease.

Cell Biology↗

bioRxiv2026

Genomic imprinting of the metabolic regulator gene Klf14 is regulated by a paternal sub-TAD anchored at Mest and a shared enhancer in mice.

KLF14 acts as a master regulator of gene expression in adipose tissue and variants at the human KLF14 gene show strong and reproducible association with type 2 diabetes and metabolic syndrome. Risk alleles are only pathologic when maternally inherited, consistent with the observation that KLF14/Klf14 is a maternally-expressed imprinted gene in human and mouse. However, how genomic imprinting is regulated at this important locus is currently unknown. In both species, KLF14/Klf14 is located [~]200 kb away from the paternally imprinted gene MEST/Mest, which is regulated by a maternal gametic differentially methylated region (gDMR) at its CpG island (CGI) promoter. Although the Klf14 CGI is kept unmethylated in most tissues, maternally-inherited DNA methylation (DNAme) marks are paradoxically required for Klf14 expression in mouse. Here, we show that Mest and Klf14 reside within the same topologically associating domain (TAD) in both mouse embryonic stem cells (ESCs) and differentiated cells, defined by sites of biallelic CTCF binding at the boundaries. Using allele-specific 4C-seq in F1 hybrid ESCs, we show that CTCF binding specifically to the unmethylated Mest gDMR generates a paternal allele-specific sub-TAD encompassing Klf14. We further show through CRISPR-Cas9-mediated mutagenesis, that deletions of the paternal Mest promoter region in ESCs as well as in vivo in mutant mice, results in both loss of Mest expression and acquisition of biallelic expression at Klf14. By analyzing epigenetic marks and chromatin looping in the Klf14-expressing pituitary cell line AtT-20, we identify a putative enhancer element shared by Mest and Klf14, providing a mechanistic model for the regulation of Klf14 imprinting. This work defines a new role for the Mest maternally methylated gDMR, revealing that it exerts long-range effects via allele-specific modulation of TAD structures and consequently act as an imprinting control region (ICR) in the regulation of Klf14 imprinting. Conservation of this TAD organisation at the human locus suggests that a similar regulatory mechanism operates at KLF14.

developmental biology↗

bioRxiv2026

Toward Computationally Complete Spatial Omics

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

genomics↗

bioRxiv2025

Multi-ancestry Transcriptome-Wide Association Study Reveals Shared and Population-Specific Genetic Effects in Alzheimer's Disease

Alzheimers disease (AD) risk differs across ancestral populations, yet most genetic studies have focused on non-Hispanic White (NHW) cohorts. We conducted a multi-population transcriptome-wide association study (TWAS) using whole-blood RNA-seq and genotype data from NHW (n=235), African American (AA; n=224), and Hispanic (HISP; n=292) MAGENTA participants. Using SuShiE for multi-population cis-eQTL fine-mapping, we identified credible sets for 8,748 genes, improving fine-mapping precision relative to analyses using fewer populations. cis-eQTL effects were largely shared across populations, with a subset showing population-specific regulation. We performed population-stratified TWAS of AD and inverse variance-weighted meta-analysis, followed by gene-level TWAS fine-mapping (MA-FOCUS), prioritizing nine genes (FDR<0.05, PIP>0.8), including established AD loci (BIN1, PTK2B, DMPK) with broadly consistent effects across populations. At BIN1, fine-mapped cis-eQTL variants used in the TWAS prediction model highlighted rs11682128, which is only modestly correlated with the GWAS index SNP rs6733839 (r2 {approx} 0.34), demonstrating how integrating eQTL fine-mapping with TWAS can refine signals beyond sentinel GWAS variants. We also identified an association between COG4 expression and AD in NHW, implicating Golgi-related pathways. Using independent SuShiE-derived models from TOPMed MESA (PBMC), several signals replicated directionally across ancestries, with the strongest statistical support in NHW. Overall, multi-population eQTL fine-mapping improves model interpretability and helps resolve shared and population-specific regulatory mechanisms relevant to AD.

genomics↗

bioRxiv2025

Sex-Stratified Transcriptomic Meta-Analysis of Alzheimer's Disease Reveal Brain Region and Sex Specific Dysregulation

ObjectiveAlzheimer disease (AD) is a neurodegenerative disorder leading to cognitive decline. Despite growing recognition of sex differences in epidemiology, symptomatology, and clinical outcomes of AD, the molecular mechanisms underlying these variations remain poorly defined. We performed transcriptome association studies of AD aiming to identify sex-specific and sex-dependent transcriptomic profiles that could provide insights into the molecular mechanisms underlying sex differences in AD pathogenesis. MethodsWe conducted a meta-analysis of bulk-RNAseq data derived from human postmortem brain studies. Specifically, we analyzed gene expression differences between individuals diagnosed with AD and non-cognitively impaired (NCI) individuals across two key brain regions: the prefrontal cortex and the temporal lobe. We performed stratified differential expression analyses separately in males and females, alongside combined analyses across sexes. Additionally, we assessed the data in relation to known AD genes, proteomic studies, and drug repurposing opportunities. ResultsBeyond the genes commonly dysregulated across both sexes, our meta-analyses identified multiple differentially expressed genes (DEGs) between AD and NCI that are either altered in only one sex or show different effects between sexes. Some genes are known AD genes from genetic studies, but others are novel. Correlation with proteomic data suggests that these transcriptional differences have functional significance, potentially contributing to the biological mechanisms underlying sex differences observed in AD. Finally, we identify drug compounds that are potential candidates for treatment. InterpretationOur findings enhance our understanding of sex-related differences in disease etiology and progression, and underscore the importance of incorporating sex as a critical variable in transcriptomic studies of AD. These insights help pave the way for more precise, personalized medicine approaches that account for sex-specific molecular mechanisms.

molecular biology↗

bioRxiv2025

Modulation of cofilin 1 phosphorylation induces juvenile-like plasticity in the adult mouse visual cortex.

Cofilin 1 is an actin-depolymerizing protein that plays a fundamental role in actin dynamics, particularly within dendritic spines, where it has been implicated in both structural and functional plasticity. We recently demonstrated (by differential proteomics, western blot and immunohistochemistry) that the expression of cofilin 1 and its inactive phosphorylated form are dynamically regulated in the mouse visual cortex during postnatal development and by visual experience. Moreover, we found that cofilin 1 expression levels correlates with periods of heightened plasticity in the mouse visual cortex. In this study, we analyzed whether the pharmacological modulation of cofilin 1 activity affects plasticity processes in the visual cortex. Adult mice were treated with a synthetic peptide inhibitor of cofilin 1 activity (PCOF) or a control peptide (TAT) and then monocularly deprived of vision during 3 days. Following reopening of the deprived eye, structural plasticity was assessed by quantifying dendritic spine density using Golgi-like staining, and visual plasticity was evaluated by measuring visual acuity through the optomotor response test. Our results show that, in adult mice treated with the PCOF peptide - but not in controls - monocular deprivation led to a significant reduction in dendritic spine density in the contralateral visual cortex, as well as a decrease in visual acuity of the previously deprived eye. These findings indicate that cofilin 1 activity is crucial for the regulation of experience-dependent plasticity in the adult mouse visual cortex.

neuroscience↗

bioRxiv2025

High-Throughput Multiomics Profiling of Model Systems Using the AVITI24 Platform

We present a multiomics platform comprising Teton, a detection assay system, and AVITI24, a dual-flowcell instrument that performs both cellular imaging and sequencing readout. Teton integrates a compartmentalized flowcell for cell culture with methods to measure morphology, RNA, and protein at subcellular resolution. The platform quantifies morphological features through cell painting of 6 cellular components, RNA expression of up to 350 transcripts via sequencing of oligonucleotides hybridized to mRNA, and protein expression of up to 200 targets using antibody-linked oligonucleotide sequencing. The flow cell accommodates >1 million cells in a 10 cm squared open-well format or can be subdivided into 12 or 48 wells to support experiments with multiple conditions or time points. We describe and validate the detection methods of the platform and showcase its capabilities by co-culturing three cancer cell lines and elucidating the cellular pathways triggered by various drug treatments as a function of time. Using multiple time points enables us to capture the dynamics of cellular processes including receptor activation and signaling cascades. The results demonstrate how different cancer cells evade TNF-induced apoptosis by activating compensatory signaling programs that maintain survival despite pro-apoptotic cues. Our model system replicates previously published results and highlights the versatility of the platform in enabling rapid, high-throughput analysis of complex cellular responses in varied biological contexts.

genomics↗

bioRxiv2025

Developmental gene expression patterns driving species-specific cortical features

The cerebral cortex shows species-specific variations in size and organization, likely accounting for distinct behavioral abilities. These structural differences may reflect evolutionary changes in the developmental expression of shared genes. To investigate this possibility, we compared cell-type-specific gene expression across species in the developing mouse and human neocortex, and human cortical organoids, by generating a shared transcriptional reference framework. This identified genes with conserved/divergent expression patterns, providing a molecular foundation to interrogate species-specific cellular properties. Using this resource, we discovered that the transcription factor JUNB is expressed in human but not mouse progenitors. Through cell-type-specific gain- and loss-of-function experiments in mice and human organoids, we demonstrate that JUNB bidirectionally controls human cortical features, including progenitor proliferation rates, neuronal production timing, and total neuronal output. This reveals how cell-type-specific regulation of shared genes during development can drive species-specific cortical features, providing a framework for understanding the molecular basis of cortical evolution.

neuroscience↗

bioRxiv2024

Methylation Clocks Do Not Predict Age or Alzheimer's Disease Risk Across Genetically Admixed Individuals

Epigenetic aging clocks based on DNA methylation patterns across the genome have emerged as a potential biomarker for risk of age-related diseases, like Alzheimers disease (AD), and environmental and social stressors. However, methylation clocks have not been comprehensively validated in genetically diverse individuals. Here we evaluate a set of first-, second-, and third-generation methylation clocks in 621 AD patients and matched controls from African American, Hispanic, and White cohorts. The clocks are less accurate at predicting age in genetically admixed cohorts compared to the White cohort, especially for those with substantial African ancestry. This decreased accuracy holds in >2,500 individuals of European and African ancestry from three additional datasets. The clocks also fail to consistently identify age acceleration in admixed AD cases compared to controls. To explore potential causes for the lack of generalization of the clocks, we intersected clock CpGs with methylation, germline genetic variants, and methylation QTL (meQTL) data from global populations. We find differential methylation between African and European ancestry individuals is common for clock CpGs. Genetic variants rarely disrupt clock CpGs between populations, but a substantial fraction of clock CpGs have meQTL with significantly higher frequencies in African genetic ancestries. Our results demonstrate that methylation clocks often fail to predict age and AD risk when applied across populations and suggest avenues for improving their portability by considering differences in genetic and epigenetic patterns across human populations.

genomics↗

bioRxiv2024

Cellulose synthesis in Arabidopsis by heterologous expression of lower plants CESA proteins

Cellulose is the most abundant component of plant cell walls where it plays a pivotal role in regulating plant cell size and shape. In addition, as a component of the woody secondary cell walls, cellulose represents an abundant renewable resource to produce materials and chemicals. In higher plants, cellulose is synthesised at the plasma membrane by a hexameric protein complex, known as the rosette, that is able to synthesise 18 glucose chains that bond together to form a microfibril. While this rosette structure is highly conserved, significant variation exists in the structure and physical properties of cellulose found in different cell types and synthesised by different species. In this study, we surveyed the ability of the catalytic subunits of the cellulose synthase complex (CESA proteins) from a range of lower plant species to synthesise cellulose in the Arabidopsis secondary cell walls. Several lower plant CESA proteins are able to function in higher plants in conjunction Arabidopsis CESAs. Additionally, two moss CESA proteins synthesised cellulose in absence of Arabidopsis CESAs but with reduced crystallinity, indicating that it is the structure of CESA proteins themselves and not the cellular environment that determines the properties of the cellulose synthesised.

plant biology↗

bioRxiv2023

Parkinson's disease-derived alpha-Synuclein assemblies combined with TNFalpha and Prostaglandin E2 induces a specific chronic-type inflammatory phenotype in microglial cells

Parkinsons disease (PD) is a common age-related neurodegenerative disorder characterized by the aggregation of -synuclein (SYN) building up intraneuronal inclusions termed Lewy pathology. Mounting evidence suggests that neuron-released SYN aggregates could be central to microglial activation, which in turn mounts and orchestrates neuroinflammatory processes potentially harmful to neurons. Therefore, understanding the mechanisms that drive microglial cell activation, polarization and function in PD might have important therapeutic implications. Here, using primary microglia, we investigated the inflammatory potential of pure SYN fibrils derived from PD patients. We further explored and characterized microglial cell responses to a chronic-type inflammatory stimulation combining PD patient-derived SYN fibrils (FPD), Tumor necrosis factor- (TNF) and prostaglandin E2 (PGE2) (TPFPD). We showed that FPD hold stronger inflammatory potency than pure SYN fibrils generated de novo. When combined with TNF and PGE2, FPD polarizes microglia toward a particular functional phenotype departing from FPD-treated cells and featuring lower inflammatory cytokine and higher glutamate release. Whereas metabolomic studies showed that TPFPD-exposed microglia were closely related to classically activated M1 proinflammatory cells, notably with similar tricarboxylic acid cycle disruption, transcriptomic analysis revealed that TPFPD-activated microglia assume a unique molecular signature highlighting upregulation of genes involved in glutathione and iron metabolisms. In particular, TPFPD-specific upregulation of Slc7a11 (which encodes the cystine-glutamate antiporter xCT) was consistent with the increased glutamate response and cytotoxic activity of these cells toward midbrain dopaminergic neurons in vitro. Together, these data further extend the structure-pathological relationship of SYN fibrillar polymorphs to their innate immune properties and demonstrate that PD-derived SYN fibrils, TNF and PGE2 act in concert to drive microglial cell activation toward a specific and highly neurotoxic chronic-type inflammatory phenotype characterized by robust glutamate release and iron retention.

neuroscience↗

bioRxiv2023

Fast And Accurate Population Level Transcranial Magnetic Stimulation via Low-Rank Probabilistic Matrix Decomposition (PMD)

Transcranial magnetic stimulation (TMS) is used to study brain function and treat mental health disorders. During TMS, a coil placed on the scalp induces an E-field in the brain that modulates its activity. TMS is known to stimulate regions that are exposed to a large E-field. Clinical TMS protocols prescribe a coil placement based on scalp landmarks. There are inter-individual variations in brain anatomy that result in variations in the TMS-induced E-field at the targeted region and its outcome. These variations across individuals could in principle be minimized by developing a large database of head subjects and determining scalp landmarks that maximize E-field at the targeted brain region while minimizing its variation using computational methods. However, this approach requires repeated execution of a computational method to determine the E-field induced in the brain for a large number of subjects and coil placements. We developed a probabilistic matrix decomposition-based approach for rapidly evaluating the E-field induced during TMS for a large number of coil placements. Our approach can determine the E-field induced in over 1 Million coil placements in 9.5 hours, in contrast, to over 5 years using a bruteforce approach. After the initial set-up stage, the E-field can be predicted over the whole brain within 2-3 milliseconds and to 2% accuracy. We tested our approach in over 200 subjects and achieved an error of < 2% in most and < 3.5% in all subjects. We will present several examples of bench-marking analysis for our tool in terms of accuracy and speed across and its applicability for population level optimization of coil placement. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=125 HEIGHT=200 SRC="FIGDIR/small/527758v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@1650e2dorg.highwire.dtl.DTLVardef@185e477org.highwire.dtl.DTLVardef@15a4376org.highwire.dtl.DTLVardef@10304fa_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA method for practical E-field informed population-level TMS coil placement strategies is developed. C_LIO_LIThis algorithm enables the determination of E-field informed optimal coil placement in seconds enabling its use for close-loop and on-the-fly reconfiguration of TMS. C_LIO_LIAfter the initial set-up stage of less than 10 hours, the E-field can be predicted for any coil placement across the whole brain within in 2-3 milliseconds. C_LI

neuroscience↗

bioRxiv2022

High-sensitivity calcium biosensor on the mitochondrial surface reveals that IP3R channels participate in the reticular Ca2+ leak towards mitochondria

Genetically encoded biosensors based on fluorescent proteins (FPs) are widely used to monitor dynamics and sub-cellular spatial distribution of calcium ion (Ca2+) fluxes and their role in intracellular signaling pathways. The development of different mutations in the Ca2+-sensitive elements of the cameleon probes has allowed sensitive range of Ca2+ measurements in almost all cellular compartments. Region of the endoplasmic reticulum (ER) tethered to mitochondria, named as the mitochondrial-associated membranes (MAMs), has received an extended attention since the last 5 years. Indeed, as MAMs are essential for calcium homeostasis and mitochondrial function, molecular tools have been developed to assess quantitatively Ca2+ levels in the MAMs. However, sensitivity of the first generation Ca2+ biosensors on the surface of the outer-mitochondrial membrane (OMM)do not allow to measure M or sub-M changes in Ca2+ concentration which prevents to measure the native activity (unstimulated exogenously) of endogenous channels. In this study, we assembled a new ratiometric highly sensitive Ca2+ biosensor expressed on the surface of the outer-mitochondrial membrane (OMM). It allows the detection of smaller differences than the previous biosensor in or at proximity of the MAMs. Noteworthy, we demonstrated that IP3-receptors have an endogenous activity which participate to the Ca2+ leak channel on the surface of the OMM during hypoxia or when SERCA activity is blocked.

cell biology↗

bioRxiv2020

Fast computational optimization of TMS coil placement for individualized electric field targeting

Background During transcranial magnetic stimulation (TMS) a coil placed on the scalp is used to non-invasively modulate activity of targeted brain networks via a magnetically induced electric field (E-field). Ideally, the E-field induced during TMS is concentrated on a targeted cortical region of interest (ROI).Objective To improve the accuracy of TMS we have developed a fast computational auxiliary dipole method (ADM) for determining the optimum coil position and orientation. The optimum coil placement maximizes the E-field along a predetermined direction or, alternatively, the overall E-field magnitude in the targeted ROI. Furthermore, ADM can assess E-field uncertainty resulting from precision limitations of TMS coil placement protocols.Method ADM leverages the electromagnetic reciprocity principle to compute rapidly the TMS induced E-field in the ROI by using the E-field generated by a virtual constant current source residing in the ROI. The framework starts by solving for the conduction currents resulting from this ROI current source. Then, it rapidly determines the average E-field induced in the ROI for each coil position by using the conduction currents and a fast-multipole method. To further speed-up the computations, the coil is approximated using auxiliary dipoles enabling it to represent all coil orientations for a given coil position with less than 600 dipoles.Results Using ADM, the E-fields generated in an MRI-derived head model when the coil is placed at 5,900 different scalp positions and 360 coil orientations per position (over 2.1 million unique configurations) can be determined in under 15 minutes on a standard laptop computer. This enables rapid extraction of the optimum coil position and orientation as well as the E-field variation resulting from coil positioning uncertainty.Conclusion ADM enables the rapid determination of coil placement that maximizes E-field delivery to a specific brain target. This method can find the optimum coil placement in under 15 minutes enabling its routine use for TMS. Furthermore, it enables the fast quantification of uncertainty in the induced E-field due to limited precision of TMS coil placement protocols, enabling minimization and statistical analysis of the E-field dose variability.HighlightsAuxiliary dipole method (ADM) optimizes TMS coil placement in under 8 minutesOptimum coil position is up to 14 mm away from conventional targetingOptimum coil orientation is typically near normal to the sulcal wallTMS induced E-field is less sensitive to orientation than position errorsCompeting Interest StatementThe authors have declared no competing interest.View Full Text

bioengineering↗

bioRxiv2019

Arabidopsis XTH4 and XTH9 contribute to wood cell expansion and secondary wall formation

In dicotyledons, xyloglucan is the major hemicellulose of primary walls affecting the load-bearing framework with participation of XTH enzymes. We used loss- and gain-of function approaches to study functions of abundant cambial region expressed XTH4 and XTH9 in secondary growth. In secondarily thickened hypocotyls, these enzymes had positive effects on vessel element expansion and fiber intrusive growth. In addition, they stimulated secondary wall thickening, but reduced secondary xylem production. Cell wall analyses of inflorescence stems revealed changes in lignin, cellulose, and matrix sugar composition, indicating overall increase in secondary versus primary walls in the mutants, indicative of higher xylem production compared to wild type (since secondary walls were thinner). Intriguingly, the number of secondary cell wall layers was increased in xth9 and reduced in xth4, whereas the double mutant xth4x9 displayed intermediate number of layers. These changes correlated with certain Raman signals from the walls, indicating changes in lignin and cellulose. Secondary walls were affected also in the interfascicular fibers where neither XTH4 nor XTH9 were expressed, indicating that these effects were indirect. Transcripts involved in secondary wall biosynthesis and in cell wall integrity sensing, including THE1 and WAK2, were highly induced in the mutants, indicating that deficiency in XTH4 and XTH9 triggers cell wall integrity signaling, which, we propose, stimulates the xylem cell production and modulates secondary wall thickening. Prominent effects of XTH4 and XTH9 on secondary xylem support the hypothesis that altered xyloglucan can affect wood properties both directly and via cell wall integrity sensing. SIGNIFICANCE STATEMENTXyloglucan is a ubiquitous component of primary cell walls in all land plants but has not been so far reported in secondary walls. It is metabolized in muro by cell wall-residing enzymes - xyloglucan endotransglycosylases/hydrolases (XTHs), which are reportedly abundant in vascular tissues, but their role in these tissues is unclear. Here we report that two vascular expressed enzymes in Arabidopsis, XTH4 and XTH9 contribute to the secondary xylem cell radial expansion and intrusive elongation in secondary vascular tissues. Unexpectedly, deficiency in their activities highly affect chemistry and ultrastructure of secondary cell walls by non-cell autonomous mechanisms, including transcriptional induction of secondary wall-related biosynthetic genes and cell wall integrity sensors. These results link xyloglucan metabolism with cell wall integrity pathways, shedding new light on previous reports about prominent effects of xyloglucan metabolism on secondary walls. One sentence summaryXTH4 and XTH9 positively regulate xylem cell expansion and fiber intrusive tip growth, and their deficiency alters secondary wall formation via cell wall integrity sensing mechanisms.

developmental biology↗

bioRxiv2019

coMethDMR: Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies

Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying differentially methylated regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the regions that contain consecutive highly significantly differentially methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic regions, and is available as an open-source R package.

bioinformatics↗