bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling Genomic Complexity: A Framework for Genome Graph Structural Analysis and Optimised Variant Calling Workflows
Authors: Kamaraj Venkatesh , Gupta Ayam , Raman Karthik , Narayanan Manikandan , Sinha Himanshu
Published: June 2024

Genome graphs offer a powerful alternative to linear reference genomes, as they provide a richer representation of a collection of genomes by emphasising the polymorphic regions. Despite their advantages, it is difficult to characterise the structural complexity of a genome graph and efficiently call variants using it. In our study, we developed a novel framework to visualise and quantify the structural complexity of genome graphs and optimised existing genome graph-based variant-calling workflows. We applied these techniques on two human pan-genome graphs constructed with the variants from the 1000 Genomes Project - the first augmenting only common variants and the second all the variants, including rare ones. We found that rare variants increased the variability of a genome graph by 10-fold but hypervariability by 50-fold. Our framework highlighted biologically significant and highly variable loci like HLA and DEFB and several novel variable regions. Benchmarking the optimised variant-calling workflow with the two genome graphs identified 9.83% more variants than the linear reference genome. Additionally, it showed that rare variants had minimal impact on variant-calling performance. Our methods are effective in identifying novel genomic loci and variants from genome graphs and revealing the underlying genomic complexity of the represented population or species.
Residual force enhancement decreases when scaling from the single muscle fibre to joint level in humans
Authors: Hinks Avery , Jacob Kaitlyn B. E. , Patterson Makenna A. , Dalton Benjamin E. , Power Geoffrey A.
Published: June 2024

Residual force enhancement (rFE), defined as increased isometric force following active lengthening compared to a fixed-end isometric contraction at the same muscle length and level of activation, is present across all scales of muscle. While rFE is always present at the cellular level, often rFE ‘non-responders’ are observed during joint-level voluntary contractions. We compared rFE between the joint level and single fibre level (vastus lateralis biopsies) in 16 young males.In-vivovoluntary knee-extensor rFE was measured by comparing steady-state isometric torque between a stretch-hold (maximal activation at 150°, stretch to 70°, hold) and a fixed-end isometric contraction, with ultrasonographic recording of vastus lateralis fascicle length (FL). Fixed-end contractions were performed at 67.5°, 70°, 72.5°, and 75°; the joint angle that most closely matched FL of the stretch-hold contraction’s isometric steady-state was used to calculate rFE. The starting and ending FLs of the stretch-hold contraction were expressed as % optimal FL, determined via torque-angle relationship. In single fibre experiments, the starting and ending fibre lengths were matched relative to optimal length determined fromin-vivotesting, yielding an average sarcomere excursion of ∼2.2-3.4µm. There was a greater magnitude of rFE at the single fibre (∼20%) than joint level (∼5%) (P=0.004), with ‘non-responders’ only observed at the joint level. By comparing rFE across scales within the same participants, we show the development of the rFE non-responder phenomenon is upstream of rFE’s cellular mechanisms, with rFE only lost rather than gained when scaling from single fibres to the joint level.
Genetic burden of dysregulated cytoskeletal organisation in the pathogenesis of pulmonary fibrosis
Authors: Wang Dapeng , Ni Yujie , Liu Bin , Ding Huan , John Alison , Wain Louise V , Johnson Simon R. , Maher Toby M , Molyneaux Philip L , Renzoni Elizabeth , Saini Gauri , Wells Athol U , Morris-Rosendahl Deborah , Jenkins R Gisli , Stewart Iain
Published: June 2024

Background

Pulmonary fibrosis (PF) is a shared characteristic of chronic interstitial lung diseases of mixed aetiology. Previous studies on PF highlight a pathogenic role for common and rare genetic variants. This study aimed to identify rare pathogenic variants that are enriched in distinct biological pathways and dysregulated gene expression.

Methods

Rare variants were identified using whole genome sequencing (WGS) from two independent PF cohorts, the PROFILE study and the Genomics England 100K (GE100KGP) cohort, with the gnomAD database as a reference. Four pathogenic variant categories were defined: loss of function variants, missense variants, protein altering variants, and protein truncating variants. Gene burden testing was performed for rare variants defined as having a minor allele frequency <0.1%. Overrepresentation analysis of gene ontology terms and gene concept network analysis were used to interpret functional pathways. Integration of publicly available transcriptomic datasets was performed using weighted gene co-expression network analysis of idiopathic pulmonary fibrosis (IPF) lung tissue compared with healthy controls.

Results

Burden testing was performed on 507 patients from the PROFILE study and 451 PF patients from GE100KGP cohort, compared with 76,156 control participants from the gnomAD database. Ninety genes containing significantly more pathogenic rare variants in cases than in controls were observed in both cohorts. Fifty-six genes included missense variants and 87 genes included protein altering variants. For missense variants,HMCN1, encoding hemicentin-1, andRGPD1, encoding a protein with a RanBD1 domain, were highly associated with PF in both PROFILE (p=5.70E-22 and p=4.48E-51, respectively) and GE100KGP cohorts (p=2.27E-24 and p=1.59E-36, respectively). 56 of 90 genes with significant burden were observed within modules correlated with disease in transcriptomic analysis, includingHMCN1andRGPD1. Enriched functional categories from genetic and transcriptomic analyses included pathways involving extracellular matrix constituents, cell adhesion properties and microtubule organisation.

Conclusions

Rare pathogenic variant burden testing and weighted gene co-expression network analysis of transcriptomic data provided complementary evidence for pathways regulating cytoskeletal dynamics in PF pathogenesis. Functional validation of candidates could provide novel targets for intervention strategies.
No effect of menstrual cycle phase on eccentric exercise-induced neuromuscular impairments and the magnitude of the repeated bout effect
Authors: Rilling Amelia , Power Geoffrey A.
Published: June 2024

Neuromuscular function is impaired following an unaccustomed bout of eccentric exercise, however, through the repeated bout effect (RBE) the muscle is protected from damage following a subsequent bout of eccentric exercise. As a result of unaccustomed eccentric contractions, structural muscle damage occurs in both sexes. However, the inflammatory response may be mitigated in females due to estradiol, thereby attenuating the secondary effects of muscle damage and potentially limiting the magnitude of the RBE. We investigated the relationship between menstrual cycle phase and oral contraceptive use on neuromuscular impairments following the first bout of exercise, and the magnitude of the RBE. Thirteen female participants performed two bouts of 150 maximal eccentric voluntary contractions of the elbow flexors four weeks apart. Normally menstruating females participated during the late follicular phase (day 10-14) of their menstrual cycle, as determined through cycle tracking, when estradiol is near peak, and progesterone is lower. Oral contraceptive users were tested on their placebo pill days (lower estradiol). Neuromuscular function was assessed for Bout 1 before the eccentric protocol and then again 48 hours following, and this was repeated 4 weeks later for Bout 2. Eccentric exercise-induced muscle weakness and soreness did not differ between groups following Bout 1 (p=0.885), and the magnitude of the RBE (p<0.05) was similar between groups (p=0.995). Females in the late follicular phase (classified as high estradiol) and females on combined oral contraceptives (low estradiol) had similar impairments in neuromuscular function following the first bout of eccentric exercise, and a similar RBE.
Sex-specific immunocompetence: resistance and tolerance can both be futile but not under the same circumstances
Authors: Brenninger Franziska A. , Kovalov Viktor , Kokko Hanna
Published: June 2024

Immunocompetence evolution can involve a ‘resistance is futile’ scenario, if parasite encounter rates are so high that high investment in resistance only marginally delays infection. Here, we investigate two understudied aspects of ‘futility’. First, immunocompetence is usefully categorized as reducing the rate of becoming infected (resistance) or reducing the negative fitness consequences of infection once it happened (tolerance). We compare the prospects of futility for resistance, tolerance, and their joint occurrence, showing that resistance futility arises with respect to parasite encounter rates, while tolerance futility arises with respect to parasite virulence. However, if the same host trait improves pleiotropically both resistance and tolerance, futility disappears altogether and immunity investment remains profitable when increasing parasite encounter rates, virulence, or both. Second, we examine how sexual selection strength impacts these findings. If one sex (typically males) is near the faster end of a fast-slow continuum of life histories, then life history patterns reflecting futility can evolve sex-specificity. The solutions often feature sexual dimorphism in immunocompetence, but not always in the direction of strong sexual selection yielding low immunity: sexual selection can select for faster and ‘sicker’ lives, but if sexual selection also causes traits that impact parasite encounter rates, the results are strongly dependent on whether futility (along any axis) plays a role.

Lay Summary

Intuition suggests that investment into immunity is higher, when hosts frequently encounter parasites. While there are examples that confirm this, in other cases, hosts have been shown to abandon immune defenses under high parasite pressure. We reconcile these findings by modelling the optimal host resource allocation towards immunity under varying parasite pressure and strength of sexual selection. Our results show two axes along which immunity investments are futile and should therefore be abandoned in favor of investing into reproduction: resisting infection becomes futile under high parasite abundance, while tolerating the harmful effects of infection is not beneficial under ever increasing parasitic virulence. However, investments of organisms that are capable of both resistance and tolerance mechanisms yield fitness payoffs also when parasites are highly virulent and abundant. This work highlights the impact of parasites and immune defenses on optimal immunity investment levels in hosts, an insight which also complements theory on sex-specific immunity.
Elevated rates of molecular evolution genome-wide in mutualist legumes and rhizobia
Authors: Harrison L. T , Stinchcombe J. R , Frederickson M. E
Published: June 2024

Rates of molecular evolution vary greatly among even closely related species. Although theory predicts that antagonistic interactions between species increase rates of molecular evolution, predictions for how mutualism affects evolutionary rates are mixed. Here, we compared rates of molecular evolution between 1) mutualistic and non-mutualistic legumes, 2) an independent set of symbiotic rhizobia and their non-symbiotic close relatives, and 3) symbiotic and non-symbiotic clades withinEnsifer, a diverse genus of bacteria with various lifestyles. We assembled transcriptomesde novofor 12 legume species and then calculated dN/dS ratios at orthologous genes in all species to determine if genes in mutualistic plants evolve faster or slower than in their non-mutualistic relatives. We also calculated dN/dS ratios in symbiosis genes known to be important for nodulation with rhizobia. We found that mutualists have higher rates of molecular evolution genome-wide compared to non-mutualist legumes. We next calculated dN/dS ratios in 14 bacteria species across the proteobacteria phylogeny that differ in whether they associate mutualistically with plants, using previously published data. We found that in most pairs, symbiotic rhizobia show higher dN/dS values compared to their non-symbiotic relatives. Finally, within a bacterial genus with many well-characterized mutualist species (Ensifer), we calculated dN/dS ratios in symbiotic and non-symbiotic clades and found that symbiotic lineages have higher rates of molecular evolution genome-wide, but not at genes on the symbiotic plasmid pSymB. Our results suggest that although mutualism between legumes and rhizobia is associated with elevated rates of molecular evolution genome-wide, symbiosis genes may be evolutionarily stagnant.
Combining Scalable Organ Chip Platform with Deep Learning-Based Imaging Analysis for Cancer Therapeutic Screening
Authors: Yuan Yu-Chieh , Xu Beibei , McCormack Jenna , Huang XuHai , Ma Jingzhe , Marshall Thomas , Sun Yacong , Singh Hardeep , Fanelli Alyssa , Gilbride Paige , Qian Xiaohua , Xie Zhiyong , Si Longlong , Xie Xin , Bai Haiqing
Published: June 2024

Functional precision oncology represents an emerging approach to genomic approaches by testing treatment options directly on patient-derived models. Current assays, including the use of patient-derived xenograft (PDX) and patient-derived organoid (PDOs), faces major barriers in clinical use due to technical challenges, such as standardization, cost, assay time, scalability, and faithful mimicry of patient tumor microenvironment (TME). Here, we introduce an Organ Chip (OC) device constructed entirely from thermoplastic materials, free of porous membrane or other barrier structures, and optimized for high-content imaging (HCI). This automation-compatible device supports tissue-specific extracellular matrices and coculture for a wide spectrum of organ and disease types, including the TME. As a proof-of-concept, we demonstrate the growth of pancreatic, lung, and colon cancer cell lines and primary lung cancer cells and the testing of cancer drugs in these models. HCI-based phenotypic profiling enabled accurate quantification of drug response, with better performance than traditional biochemical assays. Moreover, we developed a deep-learning method for assessing drug responses using bright field images. The integration of a low-cost, scalable, and faithful OC models with automatic high-content image analysis represents a significant stride towards functional precision oncology and cancer drug discovery.
Stat3-mediated Atg7 expression enhances anti-tumor immunity in melanoma
Authors: Zimmerman Sarah M. , Suh Erin , Smith Sofia R. , Souroullas George P.
Published: June 2024

Epigenetic modifications to DNA and chromatin control oncogenic and tumor suppressive mechanisms in melanoma. EZH2, the catalytic component of the Polycomb repressive complex 2 (PRC2), which mediates methylation of lysine 27 on histone 3 (H3K27me3), can regulate both melanoma initiation and progression. We previously found that mutantEzh2Y641Finteracts with the immune regulator Stat3 and together they affect anti-tumor immunity. However, given the numerous downstream targets and pathways affected by EZH2, many mechanisms that determine its oncogenic activity remain largely unexplored. Using genetically engineered mouse models we further investigated the role of pathways downstream of EZH2 in melanoma carcinogenesis and identified significant enrichment in several autophagy signatures, along with increased expression of autophagy regulators, such as Atg7. In this study, we investigated the effect of Atg7 on melanoma growth and tumor immunity within the context of anEzh2Y641Fepigenetic state. We found that expression of Atg7 is largely dependent on Stat3 expression and that deletion of Atg7 slows down melanoma cell growthin vivo, but notin vitro. Atg7 deletion also results in increased CD8+ T cells and reduced myelosuppressive cell infiltration in the tumor microenvironment, suggesting a strong immune system contribution in the role of Atg7 in melanoma progression. These findings highlight the complex interplay between genetic mutations, epigenetic regulators, and autophagy in shaping tumor immunity in melanoma.
Steady-state, therapeutic, and helminth-induced IL-4 compromise protective CD8 T cell bystander activation
Authors: Maurice Nicholas J , Dalzell Talia S , Jarjour Nicholas N , DePauw Taylor A , Jameson Stephen C
Published: June 2024

Memory CD8 T cells (Tmem) can be activated into innate-like killers by cytokines like IL-12, IL-15, and/or IL-18; but mechanisms regulating this phenomenon (termed bystander activation) are not fully resolved. We found strain-intrinsic deficiencies in bystander activation using specific pathogen-free mice, whereby basal IL-4 signals antagonize IL-18 sensing. We show that therapeutic and helminth-induced IL-4 impairs protective bystander-mediated responses against pathogens. However, this IL-4/IL-18 axis does not completely abolish bystander activation but rather tunes the expression of direct versus indirect mediators of cytotoxicity (granzymes and interferon-γ, respectively). We show that antigen-experience overrides strain-specific deficiencies in bystander activation, leading to uniform IL-18 receptor expression and enhanced capacity for bystander activation/cytotoxicity. Our data highlight that bystander activation is not a binary process but tuned/deregulated by other cytokines that are elevated by contemporaneous infections. Further, our findings underscore the importance of antigen-experienced Tmemto dissect the contributions of bystander Tmemin health and disease.
Multimodal Phasor Approach to study breast cancer cells invasion in 3D spheroid model
Authors: Tedeschi Giulia , Palomba Francesco , Scipioni Lorenzo , Digman Michelle A.
Published: June 2024

We implemented a multimodal set of functional imaging techniques optimized for deep-tissue imaging to investigate how cancer cells invade surrounding tissues and how their physiological properties change in the process. As a model for cancer invasion of the extracellular matrix, we created 3D spheroids from triple-negative breast cancer cells (MDA-MB-231) and non-tumorigenic breast epithelial cells (MCF-10A). We analyzed multiple hallmarks of cancer within the same spheroid by combining a number of imaging techniques, such as metabolic imaging of NADH by Fluorescence Lifetime Imaging Microscopy (NADH-FLIM), hyperspectral imaging of a solvatochromic lipophilic dye (Nile Red) and extracellular matrix imaging by Second Harmonic Generation (SHG). We included phasor-based bioimage analysis of spheroids at three different time points, tracking both morphological and biological properties, including cellular metabolism, fatty acids storage, and collagen organization. Employing this multimodal deep-imaging framework, we observed and quantified cancer cell plasticity in response to changes in the environment composition.
Functional Changes to Achilles Tendon and Enthesis in a Mouse Model of an Adolescent Masculine Gender-Affirming Hormone Treatment
Authors: Hold LeeAnn A. , Phillips Tessa , Cordts Paige , Steltzer Steph , Bae Seung-Ho , Henry Brandon , Migotsky Nicole , Grossman Sydney , Cruz Cynthia Dela , Padmanabhan Vasantha , Moravek Molly , Shikanov Ariella , Abraham Adam C. , Killian Megan L.
Published: June 2024

Many transgender youth seek gender affirming care, such as puberty suppression, to prolong decision-making and to align their physical sex characteristics with their gender identity. During peripubertal growth, connective tissues such as tendon rapidly adapt to applied mechanical loads (e.g., exercise) yet if and how tendon adaptation is influenced by sex and gender affirming hormone therapy during growth remains unknown. The goal of this study was to understand the how pubertal suppression influences the structural and functional properties of the Achilles tendon using an established mouse model of transmasculine gender affirming hormone therapy. C57BL/6N female-born mice were assigned to experimental groups to mimic gender-affirming hormone therapy in human adolescents, and treatment was initiated prior to the onset of puberty (at postnatal day 26, P26). Experimental groups included controls and mice serially treated with gonadotropin release hormone analogue (GnRHa), delayed Testosterone (T), or GnRHa followed by T. We found that puberty suppression using GnRHa, with and without T, improved the overall tendon load capacity in female-born mice. Treatment with T resulted in an increase in the maximum load that tendon can withstand before failure. Additionally, we found that GnRHa, but not T, treatment resulted in a significant increase in cell density at the Achilles enthesis.

NEW & NOTEWORTHY

These findings demonstrate that puberty suppression or testosterone does not negatively influence tendon structural or functional properties in a mouse model of transmasculine gender affirming care. In all treatment groups, the ability of the tendon to withstand load was significantly increased. Puberty suppression with GnRHa significantly increased enthesis cell density, suggesting an extended growth phase. These findings elucidate the effects of gender affirming care on the structural and functional properties of the tendon and enthesis.
Contrastive pre-training for sequence based genomics models
Authors: Sokolova Ksenia , Chen Kathleen M , Troyanskaya Olga
Published: June 2024

Motivation: In recent years deep learning has become one of the central approaches in a number of applications, including many tasks in genomics. However, as models grow in depth and complexity, they either require more data or a strategic initialization technique to improve performance. Results: In this project, we introduce cGen, a novel unsupervised, model-agnostic contrastive pre-training method for sequence-based models. cGen can be used before training to initialize weights, reducing the size of the dataset needed. It works through learning the intrinsic features of the reference genome and makes no assumptions on the underlying structure. We show that the embeddings produced by the unsupervised model are already informative for gene expression prediction and that the sequence features provide a meaningful clustering. We demonstrate that cGen improves model performance in various sequence-based deep learning applications, such as chromatin profiling prediction and gene expression. Our findings suggest that using cGen, particularly in areas constrained by data availability, could improve the performance of deep learning genomic models without the need to modify the model architecture.
HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo
Authors: Chang Ting-Ya , Waxman David J
Published: June 2024

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues. Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimalAlbuminpromoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ∼50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3). HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.
Suppression of T cell function by phosphoethanolamine, a metabolite enriched in tumor interstitial fluid
Authors: Wang Yupeng , Wilfahrt Drew , Cai Chufan , Lontos Konstantinos , Cameron Benjamin , Xie Bingxian , Peralta Ronal M. , AminiTabrizi Roya , Shah Hardik , Rivadeneira Dayana B. , Muir Alexander , Delgoffe Greg M.
Published: June 2024

Nutrient stress represents a significant barrier for antitumor immunity, and tumor interstitial fluid (TIF) often contains metabolites that hinder immune function. However, it is difficult to isolate the effects of tumor nutrient stress from other suppressive factors. Thus, we employed a chemically-defined cell culture medium based on the metabolomic profile of TIF: Tumor Interstitial Fluid Medium (TIFM). Culture of CD8+T cells in TIFM limited cell expansion and impaired CD8+T cell effector functions upon restimulation, suggesting tumor nutrient stress alone is sufficient to drive T cell dysfunction. We identified phosphoethanolamine (pEtn), a phospholipid intermediate, as a driver of T cell dysfunction. pEtn dampened TCR signaling by depleting T cells of diacylglycerol required for TCR signal transduction. Reduction of pEtn accumulation in tumors improved intratumoral T cell function and tumor control, suggesting pEtn accumulation plays a dominant role in TME immunosuppression.
Metabolomic Profiling and Characterization of a Novel 3D Culture System for Studying Chondrocyte Mechanotransduction
Authors: Brahmachary Priyanka P. , Erdogan Ayten E. , Myers Erik P. , June Ronald K.
Published: June 2024

Background/Objective

Articular chondrocytes synthesize and maintain the avascular and aneural articular cartilage.In vivothese cells are surrounded by a 3D pericellular matrix (PCM) containing predominantly collagen VI. The PCM protects chondrocytes and facilitates mechanotransduction. PCM stiffness is critical in transmitting biomechanical signals to chondrocytes. Various culture systems with different hydrogels are used to encapsulate chondrocytes for 3D culture, but many lack either the PCM or thein vivostiffness of the cartilage matrix. This study aimed at establishing a culture system to investigate a) if chondrocytes cultured in alginate will develop a PCM and b) study mechanotransduction via metabolic changes induced in 3D agarose-embedded chondrocytes upon mechanical stimulation.

Methods

We cultured primary human and bovine chondrocytes in monolayers or as alginate encapsulated cells in media containing sodium L-ascorbate. PCM expression was analyzed by immunofluorescence and western blots. We further characterized the response of chondrocytes embedded in physiologically stiff agarose to dynamic compression through metabolomic profiling.

Results

We found that primary human and bovine chondrocytes, when cultured in alginate beads with addition of sodium L-ascorbate for 7 days, had a pronounced PCM, retained their phenotype, and synthesized both collagens VI and II. This novel culture system enables alginate-encapsulated chondrocytes to develop a robust PCM thereby creating a model system to study mechanotransduction in the presence of an endogenous PCM. We also observed distinct compression-induced changes in metabolomic profiles between the monolayer-agarose and alginate-released agarose-embedded chondrocytes indicating physiological changes in cell metabolism.

Conclusion/Significance

These data show that 3D preculture of chondrocytes in alginate before encapsulation in physiologically stiff agarose leads to pronounced development of pericellular matrix that is sustained in the presence of ascorbate. This model can be useful in studying the mechanism by which chondrocytes respond to cyclical compression and other types of loading simulatingin vivophysiological conditions.
Chromosome-level genome assemblies for two quinoa inbred lines from northern and southern highlands of Altiplano where quinoa originated
Authors: Kobayashi Yasufumi , Hirakawa Hideki , Shirasawa Kenta , Nishimura Kazusa , Fujii Kenichiro , Oros Rolando , Almanza Giovanna R. , Nagatoshi Yukari , Yasui Yasuo , Fujita Yasunari
Published: June 2024

Quinoa, an annual allotetraploid plant native to the Andean highlands of South America, is emerging as an important seed crop for global food and nutrition security due to its ability to grow in marginal environments and its excellent nutritional properties. Because quinoa is partially allogamous, we have developed quinoa inbred lines necessary for molecular genetic analysis. Our comprehensive genomic analysis showed that the quinoa inbred lines fall into three genetic subpopulations: northern highland, southern highland, and lowland. Lowland and highland quinoa are the same species, but have very different genotypes and phenotypes. Lowland quinoa has relatively small grains and a darker grain color, and is widely tested and grown around the world. In contrast, the white, large-grained highland quinoa is grown in the Andean highlands, including the region where quinoa originated, and is exported worldwide as high-quality quinoa. Recently, we have shown that viral vectors can be used to regulate endogenous genes in quinoa, paving the way for functional genomics of quinoa. However, although a high-quality assembly has recently been reported for a lowland quinoa line, genomic resources of the quality required for functional genomics are not available for highland quinoa lines. Here we present high-quality chromosome-level genome assemblies for two highland inbred quinoa lines, J075 representing the northern highland line and J100 representing the southern highland line, using PacBio HiFi sequencing and dpMIG-seq. The assembled genome sizes of J075 and J100 are 1.29 and 1.32 Gb, with contigs N50 of 66.3 and 12.6 Mb, and scaffold N50 of 71.2 and 70.6 Mb, respectively, comprising 18 pseudochromosomes. The repetitive sequences of J075 and J100 represent 72.6% and 71.5% of the genome, the majority of which are long terminal repeats (GypsyandCopia), representing 44.0% and 42.7% of the genome, respectively. Thede novoassembled genomes of J075 and J100 were predicted to contain 64,945 and 65,303 protein-coding genes, respectively. The high quality genomes of these highland quinoa lines will facilitate quinoa functional genomics research on quinoa and contribute to the identification of key genes involved in environmental adaptation and quinoa domestication.
VaxOptiML: Leveraging Machine Learning for Accurate Prediction of MHC-I & II Epitopes for Optimized Cancer Immunotherapy
Authors: T Dhanushkumar , B G Sunila , Hebbar Sripad Rama , Selvam Prasanna Kumar , Vasudevan Karthick
Published: June 2024

In the realm of cancer immunotherapy, the ability to accurately predict epitopes is crucial for advancing vaccine development. Here, we introduce VaxOptiML (available athttps://vaxoptiml.streamlit.app/), an integrated pipeline designed to enhance epitope prediction and prioritization. Utilizing a curated dataset of experimentally validated epitopes and sophisticated machine learning techniques, VaxOptiML features three distinct models that predict epitopes from target sequences, pair them with personalized HLA types, and prioritize them based on immunogenicity scores. Our rigorous process of data cleaning, feature extraction, and model building has resulted in a tool that demonstrates exceptional accuracy, sensitivity, specificity, and F1-score, surpassing existing prediction methods. The robustness and efficacy of VaxOptiML are further illustrated through comprehensive visual representations, underscoring its potential to significantly expedite epitope discovery and vaccine design in cancer immunotherapy, Additionally, we have deployed the trained ML model using Streamlit for public usage, enhancing accessibility and usability for researchers and clinician.
Vasoactive Intestinal Peptide Amphiphile Micelle Material Properties Influence Their Cell Association and Internalization
Authors: Wang Xiaofei , Barcellona Agustin T. , Nowruzi Fateme , Brandt Kambrie , Schulte Megan C. , Kruse Luke E. , Dong Eric , Ulery Bret D.
Published: June 2024

Vasoactive intestinal peptide (VIP) is a promising anti-inflammatory peptide therapeutic that is known to induce biological effects by interacting with its cognate receptor (i.e., VPAC) on the surface of antigen presenting cells (APCs). For VIP-based drug delivery technologies like nano- and microparticles, little is known about the effect VPAC targeting has on APC behavior. This is further influenced by the fact that particulate material properties including chemistry, shape, and size are all known to influence APC behavior. In this study, peptide amphiphile micelles (PAMs) were employed as a modifiable platform to study the impact VPAC targeting and physical particle properties have on their association with macrophages. VIP amphiphile micelles (VIPAMs) and their scrambled peptide amphiphile micelle analogs (SVIPAMs) were fabricated from various chemistries yielding particle batches that were comprised of spheres (10 - 20 nm in diameter) and/or cylinders of varying lengths (i.e., 20 - 9000 nm). Micelle surface attachment to and internalization by macrophages were observed using confocal microscopy and their association was characterized by flow cytometry. The enclosed work provides strong evidence that macrophages rapidly bind VPAC specific micelles independent of physical properties though micelle shape and size as well as receptor-specificity all influence their long-term macrophage association. Specifically, a mixture of spherical and short cylindrical VIPAMs were able to achieve the greatest cell association which may correlate to their capacity to fully bind the VPAC receptors available on the surface of macrophages. These results provide the foundation of how nano- and microparticle physical properties and targeting capacity synergistically influence their capacity to associate with APCs.
A tool for mapping medical narratives into medical ontologies in low resource settings: A case study for German
Authors: Mustafa Faizan E , Diaz Ochoa Juan G.
Published: June 2024

Named Entity Recognition (NER) is extremely relevant in the clinical field since it allows the extraction of information, such as diagnoses or medical procedures, from non-structured data (doctor’s letters, vignettes, etc.) and coding them based on international classification systems. As a result, language models should be trained to recognize and classify these items accurately. While Large Language Models (LLMs) like ChatGPT are capable of recognizing medical entities in texts, they are not reliable at performing this task. Unlike English, where there are a variety of resources to assist with this task, other languages, such as German, lack appropriate language models. This study presents a methodology for the generation of high-quality full-synthetic datasets and the implementation of a workflow for the identification and classification of diseases, co-diseases, and medical procedures for clinical narratives in oncology.
Differential Results of Polygenic Risk Scoring for Multiple Sclerosis in European and African American Populations
Authors: Rivier Cyprien A. , Payabvash Seyedmehdi , Zhao Hongyu , Hafler David A. , Falcone Guido J. , Longbrake Erin E.
Published: June 2024

Importance

The risk of multiple sclerosis (MS) is significantly influenced by polygenic inheritance. Polygenic risk scores (PRS) for MS can help identify high-risk individuals and stratify populations for clinical trials. However, most genome-wide association studies (GWAS) have been conducted in populations of European ancestry, raising questions about the accuracy of these PRS in other ancestries.

Objective

To determine whether a PRS for MS can effectively stratify individuals of non-European ancestries.

Design, setting and participants

This cross-sectional study utilized prospectively collected data from the All of Us Research Program (2018-2023). It included participants who had both whole genome sequencing and electronic health record (EHR) data.

Exposure(s)

A PRS comprising 282 independent single nucleotide variants for MS, divided into quintiles.

Main Outcome(s) and Measure(s)

Prevalence of multiple sclerosis ascertained through ICD-10 or SNOMED codes.

Results

In this study population, MS cases comprised 1.0% (327 cases) of the European population, 0.56% (183 cases) of the African population, and 0.46% (150 cases) of the Latino/admixed American population. In analyses adjusting for age, sex, and genetic principal components, the PRS associates with MS risk in the European population, with a 141% increase in the risk of MS for individuals in the highest compared to the lowest PRS quintile (OR: 2.41 [1.69-3.50], test-for-trend p<0.001). Similarly, the PRS appropriately partitions the Latino/admixed population into increasing MS risk groups (OR: 2.56 [1.45-4.78], test-for-trend p-value <0.001). However, it did not significantly stratify the African population into distinct MS risk categories (OR: 1.45 [0.95-2.25], test-for-trend p=0.10).

Conclusions and Relevance

A PRS for MS effectively stratified individuals of European and Latino/admixed ancestries but not African ancestry. This highlights the need for ancestry-specific PRS development to ensure accurate risk prediction across diverse populations, emphasizing the importance of including non-European groups in MS genetic research.
Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci
Authors: Xu Hanfei , Gupta Shreyash , Dinsmore Ian , Kollu Abbey , Cawley Anne Marie , Anwar Mohammad Y. , Chen Hung-Hsin , Petty Lauren E. , Seshadri Sudha , Graff Misa , Below Piper , Brody Jennifer A. , Chittoor Geetha , Fisher-Hoch Susan P. , Heard-Costa Nancy L. , Levy Daniel , Lin Honghuang , Loos Ruth JF. , Mccormick Joseph B. , Rotter Jerome I. , Mirshahi Tooraj , Still Christopher D. , Destefano Anita , Cupples L. Adrienne , Mohlke Karen L , North Kari E. , Justice Anne E. , Liu Ching-Ti
Published: June 2024

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMIand PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2,GSTM3,SNAPC3,SPNS1,TMEM245,YPEL3, andZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results forSNAPC3andYPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA<PSNP& PMETA<PBMI) results forYPEL3in nucleus accumbens andNT5C2,SNAPC3,TMEM245,YPEL3, andZNF646in liver. The identified genes help link the genetic variation at obesity risk loci to biological mechanisms and health outcomes, thus translating GWAS findings to function.
A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among TNFSF superfamily in breast cancer
Authors: Moradi Abolfazl , Vafadar Esfahani Farinaz , Mohammadian Ali
Published: June 2024

Breast cancer (BC) is one of most important mortality factors among women therefore to find important genes in BC can help early diagnosis, treatment or prevention.TNFSFor tumor necrosis factor Superfamily have an important role in various cancers. In BC, some of studies have found dual roles for these genes. In this research, we conducted a comprehensive and detailed bioinformatics study on this family. UALCAN, TNMplot, UCSC Xena, GEPIA, The Human Protein Atlas, Kaplan–Meier plotter, bc-GenExMiner, cBioPortal, STRING, GeneMANIA, Enrichr, TIMER and shinyDepMap were used for analysis. We found that these genes play their role through the immune system and the high expression of eightFASLG, LTB, TNF, TNFSF8, TNFSF10, TNFSF11, TNFSF12, TNFSF13genes were positively associated with OS and RFS. Overall, our data showed that these genes can be considered as prognostic biomarkers. Further, our results suggest that this family has anti-tumor activity.
Geospatial analysis of malaria burden in Kagera region, North-western Tanzania using health facility and community survey data
Authors: Petro Daniel A. , Shaban Nyimvua , Aaron Sijenunu , Chacky Frank , Lazaro Samwel , Boni Maciej F. , Ishengoma Deus S.
Published: June 2024

Generating evidence of malaria burden in areas with confirmed artemisinin partial resistance (ART-R) is the first step before developing a response strategy to the resistance. In this study, we assessed the burden of malaria in Kagera region (with recently confirmed ART-R) by geospatial analysis using data from health facilities (HFs) and community surveys from 2017 to 2023. In 2983717/8124363 patients from HFs, rapid diagnostic test positivity rate was 36.7% (range: 0-80%) and was similar in patients aged under-fives (33.1%, range: 0-79%) and ≥5 years (33.7%, range: 3-80%). The prevalence of malaria was 10.0% (range: 0-40.5%, n=84999/ 853761) in pregnant women but it was 26.1% (3409/13065) in school children (range: 0-78.4%). We identified hotspots and coldspots, and persistently high burden in 69/192 wards, school children, and patients aged ≥5 years, providing evidence for planning and developing an ART-R response for the region.
Viral diversiy within marine biofilms and their potential roles in microbially influenced corrosion
Authors: Li Chengpeng , Zhang Yimeng , Jiang Shuqing , Shi Wenqing , Peng Yongyi , Han Yingchun , Dong Xiyang , Zhang Ruiyong
Published: June 2024

In marine environments, a wide variety of microbes exert an important influence on the corrosion of materials. Viruses are widely distributed in biofilms formed on materials and may influence the corrosion process through interactions with key corrosive microbes. However, our understanding of the viral communities within biofilms and their implications for corrosion remains notably limited. To fill this knowledge gap, we utilized 53 publicly metagenomes to investigate the ecological dynamics of viruses within biofilms on 8 different materials and their potential roles in the corrosion of materials. In biofilms, the type of materials may be the primary factor driving differences in the diversity of viral communities. Viruses within biofilms predominantly belong toCaudoviricetes,and phylogenetic analysis ofCaudoviricetesand protein-sharing networks with other environments revealed the presence of numerous novel viral clades in biofilms. The presence of virus‒host linkages revealed a close association between viruses and corrosive microbes in biofilms. Viruses play a key role in corrosion by modulating host corrosion-related metabolism. It was observed that viruses could enhance host resistance to metals and antibiotics via horizontal gene transfer. Furthermore, viruses can protect themselves from host antiviral systems through anti-defense systems. Overall, this work illustrates the diversity of viruses within biofilms formed on materials and the intricate interactions between viruses and corrosive microbes, revealing the potential roles of viruses in microbially influenced corrosion.
Analysis-ready VCF at Biobank scale using Zarr
Authors: Czech Eric , Millar Timothy R. , Tyler Will , White Tom , Elsworth Benjamin , Guez Jérémy , Hancox Jonny , Jeffery Ben , Karczewski Konrad J. , Miles Alistair , Tallman Sam , Unneberg Per , Wojdyla Rafal , Zabad Shadi , Hammerbacher Jeff , Kelleher Jerome
Published: June 2024

Background

Variant Call Format (VCF) is the standard file format for interchanging genetic variation data and associated quality control metrics. The usual row-wise encoding of the VCF data model (either as text or packed binary) emphasises efficient retrieval of all data for a given variant, but accessing data on a field or sample basis is inefficient. Biobank scale datasets currently available consist of hundreds of thousands of whole genomes and hundreds of terabytes of compressed VCF. Row-wise data storage is fundamentally unsuitable and a more scalable approach is needed.

Results

Zarr is a format for storing multi-dimensional data that is widely used across the sciences, and is ideally suited to massively parallel processing. We present the VCF Zarr specification, an encoding of the VCF data model using Zarr, along with fundamental software infrastructure for efficient and reliable conversion at scale. We show how this format is far more efficient than standard VCF based approaches, and competitive with specialised methods for storing genotype data in terms of compression ratios and single-threaded calculation performance. We present case studies on subsets of three large human datasets (Genomics England:n=78,195; Our Future Health:n=651,050; All of Us:n=245,394) along with whole genome datasets for Norway Spruce (n=1,063) and SARS-CoV-2 (n=4,484,157). We demonstrate the potential for VCF Zarr to enable a new generation of high-performance and cost-effective applications via illustrative examples using cloud computing and GPUs.

Conclusions

Large row-encoded VCF files are a major bottleneck for current research, and storing and processing these files incurs a substantial cost. The VCF Zarr specification, building on widely-used, open-source technologies has the potential to greatly reduce these costs, and may enable a diverse ecosystem of next-generation tools for analysing genetic variation data directly from cloud-based object stores, while maintaining compatibility with existing file-oriented workflows.

Key Points

VCF is widely supported, and the underlying data model entrenched in bioinformatics pipelines.

The standard row-wise encoding as text (or binary) is inherently inefficient for large-scale data processing.

The Zarr format provides an efficient solution, by encoding fields in the VCF separately in chunk-compressed binary format.