bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bioinformatics Analysis of next generation sequencing data for Risk Prediction in Patients with Type 1 diabetes mellitus
Authors: Vastrad Basavaraj , Vastrad Chanabasayya 
Published: March 2022

AbstractType 1 diabetes mellitus (T1DM) comprise the most common forms of autoimmune disease. The aim of this investigation was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of T1DM. The next generation sequencing (NGS) dataset GSE182870 was downloaded from the gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the functional enrichment, gene ontology (GO) and REACTOME pathway of the differentially expressed genes. Protein-protein interaction (PPI) network, modules, miRNA- hub gene regulatory network, and TF-hub gene regulatory network were conducted via comprehensive target prediction and network analyses. Finally, hub genes were validated by using receiver operating characteristic curve analysis. A total of 860 DEGs were screened out from NGS dataset, among which 477 genes were up regulated and 383 genes were down regulated. GO enrichment analysis indicated that up regulated genes were mainly involved in cellular metabolic process, intracellular anatomical structure and catalytic activity, and the down regulated genes were significantly enriched in cellular nitrogen compound biosynthetic process, protein containing complex and heterocyclic compound binding. REACTOME pathway enrichment analysis showed that the up regulated genes were mainly enriched in metabolism of carbohydrates and the down regulated genes were significantly enriched in metabolism of RNA. A PPI network, modules, miRNA-hub gene regulatory network and TF - hub gene regulatory network were constructed, and hub genes (MAPK14, RHOC, MAD2L1, TAF1, TRAF2, HSP90AA1, TP53, HSP90AB1, UBA52 and RACK1) were identified. This study provides further insights into the underlying pathogenesis of T1DM.
Characterization of Quantum Dots with Hyperspectral Fluorescence Microscopy for Multiplexed Optical Imaging of Biomolecules
Authors: Zhang Shuyan , Xin Cheng Joseph Yong , Chua Jian Jun , Olivo Malini 
Published: March 2022

ABSTRACTThe optical properties of quantum dots were extensively characterized using a hyperspectral fluorescence microscopy system. The system provides a single excitation wavelength in the ultraviolet and 311 emission wavelength channels in the visible. This allows detection of multiple fluorophores (e.g. different quantum dots) with a high spectral resolution in one go which is not achievable with a conventional fluorescence microscope where different filter sets have to be used. A spectral library was established based on the spectral profiles of six types of quantum dots. Notably, a slight spectral shift was observed for all samples while the sample was drying. Subsequently, two quantum dot mixture samples were studied. Using the spectral unmixing approach, the relative proportions of each quantum dot within a homogeneous mixture and the spatial distribution of each quantum dot within a heterogeneous mixture were calculated. The calculated values match well with the theoretical predictions. Hence, the analysis method presented here can be used for simultaneous imaging of multiple fluorophores using hyperspectral imaging technology. The results provide valuable information for the realization of real-time multi-channel in vivo fluorescent imaging of biomolecules.
POU2AF2/C11orf53 functions as a co-activator of POU2F3 by maintaining chromatin accessibility and enhancer activity
Authors: Szczepanski Aileen Patricia , Tsuboyama Natsumi , Zhao Zibo , Wang Lu 
Published: March 2022

AbstractSmall cell lung cancer (SCLC), accounting for around 13% of all lung cancers, often results in rapid tumor growth, early metastasis, and acquired therapeutic resistance. The POU class 2 homeobox 3 (POU2F3) is a master regulator of tuft cell identity and defines a subtype of SCLC tumors (SCLC-P subtype) that lack the expression of neuroendocrine (NE) markers. Here, we have identified a previously uncharacterized protein, C11orf53, which is co-expressed with POU2F3 in both SCLC cell lines and patient samples, defining the same SCLC-P subtype. C11orf53 is an essential gene for the cell survivability of SCLC-P subtype, based on genome-wide CRISPR screening and genetic depletion of C11orf53 or POU2F3, inducing apoptosis in different SCLC-P subtype cell lines. Furthermore, our biochemical and genome-wide studies have demonstrated that C11orf53 is a novel chromatin-bound protein that occupies broad active enhancer domains and regulates gene expression at active enhancers. Mechanistically, C11orf53 directly interacts with POU2F3 at the POU domain, and is recruited to chromatin by POU2F3. Consequently, depletion of C11orf53 dramatically reduced enhancer H3K27ac levels and chromatin accessibility, resulting in a reduction of the expression of POU2F3-dependent tuft cell markers. Based on the expression pattern and molecular function of C11orf53, we have renamed it as “POU Class 2 Homeobox Associating Factor 2” (POU2AF2). In summary, our study has identified a new co-activator of POU2 family transcription factors, and sheds light on the therapeutic potential of targeting POU2AF2/POU2F3 heterodimer in human SCLC.
Towards reliable quantification of cell state velocities
Authors: Marot-Lassauzaie Valérie , Bouman Brigitte Joanne , Donaghy Fearghal Declan , Haghverdi Laleh 
Published: March 2022

AbstractA few years ago, it was proposed to use the simultaneous quantification of unspliced and spliced messenger RNA (mRNA) to add a temporal dimension to high-throughput snapshots of single cell RNA sequencing data. This concept can yield additional insight into the transcriptional dynamics of the biological systems under study. However, current methods for inferring cell state velocities from such data (known as RNA velocities) are afflicted by several theoretical and computational problems, hindering realistic and reliable velocity estimation. We discuss these issues and propose new solutions for addressing some of the current challenges in consistency of data processing, velocity inference and visualisation. We translate our computational conclusion in two velocity analysis tools: one detailed method κ-velo and one heuristic method eco-velo.Author summarySingle cell transcriptomics has been used to study dynamical biological processes such as cell differentiation or disease progression. An ideal study of these systems would track individual cells in time but this is not directly feasible since cells are destroyed as part of the sequencing protocol. Because of asynchronous progression of cells, single cell snapshot datasets often capture cells at different stages of progression. The challenge is to infer both the overall direction of progression (pseudotime) as well as single cell specific variations in the progression. Computational methods development for inference of the overall direction are well advanced but attempts to address the single cell level variations of the dynamics are newer. La Manno et al. [1] proposed that simultaneous measurement of abundances of new (unspliced) and older (spliced) mRNA in the same single cell adds a temporal dimension to the data which can be used to infer the time derivative of single cells progression through the dynamical process. State-of-the-art methods for inference of cell state velocities from RNA-seq data (also known as RNA velocity) have multiple unaddressed issues. In this manuscript, we discuss these issues and propose new solutions. In previous works, agreement of RNA velocity estimations with pseudotime has been used as validation. We show that this in itself is not proof that the method works reliably and the overall direction of progression has to be distinguished from individual cells’ behaviour. We propose two new methods (one detailed and one cost efficient heuristic) for estimation and visualisation of RNA velocities and show that our methods faithfully capture the single-cell variances and overall trend on simulation. We further apply the methods to a dataset of developing mouse pancreas and show how the method can help us gain biological insight from real data.
Modeling of Aryl Hydrocarbon Receptor Pathway Intrinsic Immunometabolic Role using Glioblastoma Stem Cells and Patient-Derived Organoids
Authors: Watanabe Fumihiro , Hollingsworth Ethan W. , Banasavadi-Siddegowda Yeshavanth , Bartley Jenna M. , Sizemore Steven T. , Yu Lianbo , Pietrzak Maciej , Schiapparelli Paula , Puduvalli Vinay , Kaur Balveen , Quiñones-Hinojosa Alfredo , Imitola Jaime 
Published: March 2022

AbstractThe intrinsic genetic program of glioblastoma (GBM) stem cells is critical for tumor evolution and recurrence. We recently identified intrinsic phenotypes and immune-like genetic programs of GBM organoids (GBMO)1 from patient derived glioblastoma stem cells (GSCs), replicating genomic, metabolic, and cellular aspects of GBM in vivo. Aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor, is a key regulator of infiltrating immune cells in gliomas2, 3 and associated with poor prognosis, but its role in GSC biology is unknown2. Here, we show that AHR is a patient-specific regulator of the glioma intrinsic gene program in GSCs and GSC-derived GBMO that are enriched for AHR. We find that AHR is required for GSC self-renewal, GBMO expansion, radial glia-like cell proliferation, and expression of immune mediators seen in the mesenchymal subtype. CRISPR-Cas9 genetic ablation and pharmacological inhibition revealed that AHR regulates genes linked to intrinsic immunity, proliferation, and migration in GBMO. Genomic analysis of GBMO treated with AHR inhibitors identified expression signatures and candidate markers associated with survival of gliomas. Our work defines the glioma intrinsic function of AHR in a model of early GBM formation, offering a rationale for clinical exploration of a potential ‘two-hit’ target of both GBM cells and infiltrating immune cells in patients with GBM expressing high levels of AHR.
KAT5 regulates neurodevelopmental states associated with G0-like populations in glioblastoma
Authors: Mihalas Anca B. , Arora Sonali , O’Connor Samantha A. , Feldman Heather M. , Cucinotta Christine E. , Mitchell Kelly , Bassett John , Kim Dayoung , Jin Kang , Hoellerbauer Pia , Delegard Jennifer , Ling Melissa , Jenkins Wesley , Kufeld Megan , Corrin Philip , Carter Lucas , Tsukiyama Toshio , Aronow Bruce , Plaisier Christopher L. , Patel Anoop P. , Paddison Patrick J. 
Published: March 2022

SummaryIn solid tumors, G0-like states are likely critical for maintaining developmental hierarchies and cellular heterogeneity and promoting tumor growth/recurrence, yet little is known about tumor G0 states or regulation of their ingress/egress. To discover G0-like states and their regulators for glioblastoma (GBM), we analyzed G0 populations in an orthotopic model of GBM using single cell RNA-seq and performed a genome-wide CRISPR-Cas9 screen in patient-derived GBM stem-like cells (GSCs) for genes that trap cells in G0 when inhibited. We identify the protein acetyltransferase KAT5 as a key regulator of transcriptional, epigenetic, and proliferative heterogeneity impacting transitions into G0-like states. KAT5 activity suppresses the emergence of non-dividing subpopulations with oligodendrocyte progenitor and radial glial cell characteristics bothin vitroand in a human GSC brain tumor model. In primary gliomas, KAT5 activity is dynamic with KAT5lowtumor cells displaying quiescent properties, while KAT5 activity overall increases from low to high grade tumors and is associated with worse patient outcomes.
A novel class of long small RNAs associates with Argonaute1 and is up-regulated by nutrient deprivation in the alga Chlamydomonas
Authors: Li Yingshan , Kim Eun-Jeong , Voshall Adam , Moriyama Etsuko N. , Cerutti Heriberto 
Published: March 2022

AbstractSmall RNAs (sRNAs) associate with Argonaute (AGO) proteins forming effector complexes with key roles in gene regulation and defense responses against molecular parasites. In multicellular eukaryotes, extensive duplication and diversification of RNA interference (RNAi) components have resulted in intricate pathways for epigenetic control of gene expression. The unicellular alga Chlamydomonas reinhardtii also has a complex RNAi machinery, including three AGOs and three Dicer-like (DCL) proteins. However, little is known about the biogenesis and function of most endogenous sRNAs. We demonstrate here that Chlamydomonas contains uncommonly long sRNAs (>26 nt), which associate preferentially with AGO1. Somewhat reminiscent of animal PIWI-interacting RNAs, these long sRNAs are derived from moderately repetitive genomic clusters and their biogenesis appears to be Dicer-independent. Interestingly, long sRNA encoding sequences have been conserved and amplified in phylogenetically related Chlamydomonas species. Additionally, expression of several long sRNAs increases substantially under nutrient deprivation, correlating with the downregulation of predicted target transcripts. We hypothesize that the transposon-like sequences encoding long sRNAs might have been ancestrally targeted for silencing by the RNAi machinery but, during evolution, some long sRNAs might have fortuitously acquired endogenous target genes and become integrated into gene regulatory networks.
Avatar error in your favor: Embodied avatars can fix users’ mistakes without them noticing
Authors: Delahaye Mathias , Blanke Olaf , Boulic Ronan , Herbelin Bruno 
Published: March 2022

AbstractIn immersive Virtual Reality (VR), users can experience the subjective feeling of embodiment for the avatar representing them in a virtual world. This is known to be strongly supported by a high Sense of Agency (SoA) for the movements of the avatar that follows the user. In general, users do not self-attribute actions of their avatar that are different from the one they actually performed. The situation is less clear when actions of the avatar satisfies the intention of the user despite distortions and noticeable differences between user and avatar movements. A within-subject experiment was here conducted to determine whether a finger swap helping users achieve a task would be more tolerated than one penalizing them. In particular, in a context of fast-paced finger movements and with clear correct or incorrect responses, we swapped the finger animation of the avatar (e.g. user moves the index finger, the avatar moves the middle one) to either automatically correct for spontaneous mistakes or to introduce incorrect responses. Subjects playing a VR game were asked to report when they noticed the introduction of a finger swap. Results based on 3256 trials (~24% of swaps noticed) show that swaps helping users have significantly fewer odds of being noticed (and with higher confidence) than the ones penalizing users. This demonstrates how the context and the intention for motor action are important factors for the SoA and for embodiment, opening new perspectives on how to design and study interactions in immersive VR.
The motif composition of variable-number tandem repeats impacts gene expression
Authors: Lu Tsung-Yu , Smaruj Paulina N. , Fudenberg Geoffrey , Mancuso Nicholas , Chaisson Mark J.P. 
Published: March 2022

AbstractUnderstanding the impact of DNA variation on human traits is a fundamental question in human genetics. Variable number tandem repeats (VNTRs) make up roughly 3% of the human genome but are often excluded from association analysis due to poor read mappability or divergent repeat content. While methods exist to estimate VNTR length from short-read data, it is known that VNTRs vary in both length and repeat (motif) composition. Here, we use a repeat-pangenome graph (RPGG) constructed on 35 haplotype-resolved assemblies to detect variation in both VNTR length and repeat composition. We align population scale data from the Genotype-Tissue Expression (GTEx) Consortium to examine how variations in sequence composition may be linked to expression, including cases independent of overall VNTR length. We find that 9,422 out of 39,125 VNTRs are associated with nearby gene expression through motif variations, of which only 23.4% associations are accessible from length. Fine-mapping identifies 174 genes to be likely driven by variation in certain VNTR motifs and not overall length. We highlight two genes,CACNA1CandRNF213that have expression associated with motif variation, demonstrating the utility of RPGG analysis as a new approach for trait association in multiallelic and highly variable loci.
A murine model of hnRNPH2-related neurodevelopmental disorder recapitulates clinical features of human disease and reveals a mechanism for genetic compensation ofHNRNPH2
Authors: Korff Ane , Yang Xiaojing , O’Donovan Kevin , Gonzalez Abner , Teubner Brett J. W. , Nakamura Haruko , Messing James , Yang Fen , Carisey Alex , Wang Yong-Dong , Patni Tushar , Tillman Heather , Zakharenko Stanislav S. , Chook Yuh Min , Taylor J. Paul , Kim Hong Joo 
Published: March 2022

AbstractMutations inHNRNPH2cause an X-linked neurodevelopmental disorder with a phenotypic spectrum that includes developmental delay, intellectual disability, language impairment, motor function deficits, and seizures. More than 90% of patients with this disorder have a missense mutation within or adjacent to the nuclear localization signal (NLS) of hnRNPH2, although the specific pathogenic consequences of these mutations have not been examined. Here we found that hnRNPH2 NLS mutations result in reduced interaction with the nuclear transport receptor Kapβ2 in vitro and in cultured human cells. These mutations also cause modest accumulation of hnRNPH2 in the cytoplasm, suggesting that mislocalization of the protein might contribute to pathogenesis. We generated two knock-in mouse models with human-equivalent mutations in the endogenous mouse geneHnrnph2, as well asHnrnph2knockout (KO) mice, and subjected them to extensive phenotyping. Mutant knock-in mice displayed a spectrum of phenotypes that recapitulated aspects of the human disorder, including reduced survival in males, craniofacial abnormalities, impaired motor and cognitive functions, and increased susceptibility to audiogenic seizures. Mutant knock-in male mice developed more severe phenotypes than female mice, likely due to differences in X-chromosome gene dosage. In contrast, two independent lines ofHnrnph2KO mice showed no detectable phenotypes. Notably, KO mice had upregulated expression ofHnrnph1, a close paralog ofHnrnph2, whereas mutantHnrnph2knock-in mice failed to upregulateHnrnph1.Thus, genetic compensation byHnrnph1might be sufficient to counteract the loss of hnRNPH2. These findings suggest that the pathogenesis ofHNRNPH2-related disorder in humans may be driven by a toxic gain of function or a complex loss ofHNRNPH2function with impaired compensation byHNRNPH1.The mutant knock-in mice described here are an important resource for preclinical studies to assess the potential benefit of either gene replacement or therapeutic knockdown of mutant hnRNPH2.
Temporal integration of rod signals in luminance and chromatic pathways
Authors: Méndez Iñaki Cormenzana , Martín Andrés , O’Donell Beatriz , Cao Dingcai , Barrionuevo Pablo A. 
Published: March 2022

AbstractWe assessed how rod excitation (R) affects luminance (L+M+S) and chromatic [L/(L+M)] reaction times (RTs). A four-primary display based on the overlapped images of two spectrally-modified monitors, which allowed specific or combined [L+M+S+R, L/(L+M) + R] photoreceptor stimulation, was used to present a C-target stimulus differing from the background only by the selected stimulation. For the luminance pathway, rod input increased RTs, suggesting a suppressive rod-cone interaction. The responses of the chromatic pathway were faster when rods were involved, suggesting a major role of rods in mesopic color perception.
Proteomic profiling identifies co-regulated expression of splicing factors as a characteristic feature of intravenous leiomyomatosis
Authors: Krasny Lukas , Wilding Chris P , Perkins Emma , Arthur Amani , Guljar Nafia , Jenks Andrew D , Fisher Cyril , Judson Ian , Thway Khin , Jones Robin L , Huang Paul H 
Published: March 2022

AbstractIntravenous leiomyomatosis (IVLM) is a rare benign smooth muscle tumour that is characterised by intravenous growth in the uterine and pelvic veins. Previous DNA copy number and transcriptomic studies have shown that IVLM harbours unique genomic and transcriptomic alterations when compared to uterine leiomyoma (uLM), which may account for their distinct clinical behaviour. Here we undertake the first comparative proteomic analysis of IVLM and other smooth muscle tumours (comprising uLM, soft tissue leiomyoma and benign metastasising leiomyoma) utilising data-independent acquisition mass spectrometry. We show that, at the protein level, IVLM is defined by the unique co-regulated expression of splicing factors. In particular, IVLM is enriched in two clusters composed of co-regulated proteins from the hnRNP, LSm, SR and Sm classes of the spliceosome complex. One of these clusters (Cluster 3) is associated with key biological processes including nascent protein translocation and cell signalling by small GTPases. Taken together, our study provides evidence of co-regulated expression of splicing factors in IVLM compared to other smooth muscle tumours which suggests a possible role for alternative splicing in the pathogenesis of IVLM.
The link between autism and sex-specific neuroanatomy, and associated cognition and gene expression
Authors: Floris Dorothea L. , Peng Han , Warrier Varun , Lombardo Michael V. , Pretzsch Charlotte M. , Moreau Clara , Tsompanidis Alexandros , Gong Weikang , Mennes Maarten , Llera Alberto , van Rooij Daan , Oldehinkel Marianne , Forde Natalie , Charman Tony , Tillmann Julian , Banaschewski Tobias , Moessnang Carolin , Durston Sarah , Holt Rosemary J. , Ecker Christine , Dell’Acqua Flavio , Loth Eva , Bourgeron Thomas , Murphy Declan G. M. , Marquand Andre F. , Lai Meng-Chuan , Buitelaar Jan K. , Baron-Cohen Simon , Beckmann Christian F. ,   the EU-AIMS LEAP Group
Published: March 2022

ABSTRACTObjectivesThe male preponderance in autism spectrum conditions (ASC) prevalence is among the most pronounced sex ratios across different neurodevelopmental conditions. Here, we aimed to elucidate the relationship between autism and typical sex-differential neuroanatomy, cognition, and related gene expression.MethodsUsing a novel deep learning framework trained to predict biological sex, we compared sex prediction model performance across neurotypical and autistic males and females. Multiple large-scale datasets were employed at different stages of the analysis pipeline: a) Pre-training: the UK Biobank sample (>10.000 individuals); b) Transfer learning and validation: the ABIDE datasets (1,412 individuals, 5-56 years of age); c) Test and discovery: the EU-AIMS/AIMS-2-TRIALS LEAP dataset (681 individuals, 6-30 years of age) and d) Specificity: the Neuroimage and ADHD200 datasets (887 individuals, 7-26 years of age).ResultsAcross both ABIDE and LEAP we showed that features positively predictive of neurotypical males were on average more predictive of autistic males (P=1.1e-23). Features positively predictive of neurotypical females were on average less predictive of autistic females (P=1.2e-22). These accuracy differences in autism were not observed in individuals with ADHD. In autistic females the male-shifted neurophenotype was further associated with poorer social sensitivity and emotional face processing while also with associated gene expression patterns of midgestational cell types.ConclusionsOur results demonstrate a shift in both autistic male and female individuals’ neuroanatomy towards male-characteristic patterns associated with typically sex-differential, social cognitive features and related gene expression patterns. Findings hold promise for future research aimed at refining the quest for biological mechanisms underpinning the etiology of autism.