bluuebunny/crossref_metadata_2025_split huggingface dataset:
Selective sweeps influence diversity over large regions of the mouse genome
Authors: Booker Tom R. , Jackson Benjamin C. , Craig Rory J. , Charlesworth Brian , Keightley Peter D. 
Published: June 2021

AbstractTo what extent do substitutions in protein-coding versus gene-regulatory regions contribute to fitness change over time? Answering this question requires estimates of the extent of selection acting on beneficial mutations in the two classes of sites. New mutations that have advantageous or deleterious fitness effects can induce selective sweeps and background selection, respectively, causing variation in the level of neutral genetic diversity along the genome. In this study, we analyse the profiles of genetic variability around protein-coding and regulatory elements in the genomes of wild mice to estimate the parameters of positive selection. We find patterns of diversity consistent with the effects of selection at linked sites, which are similar across mouse taxa, despite differences in effective population size and demographic history. By fitting a model that combines the effects of selective sweeps and background selection, we estimate the strength of positive selection and the frequency of advantageous mutations. We find that strong positive selection is required to explain variation in genetic diversity across the murid genome. In particular, we estimate that beneficial mutations in protein-coding regions have stronger effects on fitness than do mutations in gene-regulatory regions, but that mutations in gene-regulatory regions are more common. Overall though, our parameter estimates suggest that the cumulative fitness changes brought about by beneficial mutations in protein-coding may be greater than those in gene-regulatory elements.
Variance Reducing and Noise Correction in Protein Quantification by Measuring Fluctuations in Fluorescence due to Photobleaching
Authors: Gelber Itay 
Published: June 2021

ABSTRACTQuantifying protein number using the ratio between the variance and the mean of the protein distribution is a straightforward calibration method in the experimental conditions for microscopy imaging. Recently the model has been expanded to decaying processes with binomial distribution. In this paper, we examine the model proposed, and show how the algorithm can be adapted to the case of variance in the initial number of proteins between cells. We propose improving the algorithm so that the information processing of each frame is done independently from other frames. By doing so, the variance in the process of determining the protein number can be reduced. In addition, we examine the handling of unwanted noises in the measurement, offer a solution for shot noise and background noise, and examine the expected error caused in calculating the decay constant. We also analyze the expected difficulties in conducting a practical experiment, which includes non-exponential decay, and variance in the decay constants of the cells. These methods can be applied to any superposition of n0 discrete decaying processes. However, the evaluation of expected errors in quantification is essential for early planning of the experimental conditions, and for the evaluation of the error.
Expansion of RNA sequence diversity and RNA editing rates throughout human cortical development
Authors: Cuddleston Ryn , Sloofman Laura , Liang Lindsay , Mossotto Enrico , Fan Xuanjia , Wang Minghui , Zhang Bin , Wang Jiebiao , Sestan Nenad , Devlin Bernie , Roeder Kathryn , Buxbaum Joseph D. , Sanders Stephan J. , Breen Michael S. 
Published: June 2021

ABSTRACTPost-transcriptional modifications by RNA editing are essential for neurodevelopment, yet their developmental and regulatory features remain poorly resolved. We constructed a full temporal view of base-specific RNA editing in the developing human cortex, from early progenitors through fully mature cells found in the adult brain. Developmental regulation of RNA editing is characterized by an increase in editing rates for more than 10,000 selective editing sites, shifting between mid-fetal development and infancy, and a massive expansion of RNA hyper-editing sites that amass in the cortex through postnatal development into advanced age. These sites occur disproportionally in 3’UTRs of essential neurodevelopmental genes. These profiles are preserved in non-human primate and murine models, illustrating evolutionary conserved regulation of RNA editing in mammalian cortical development. RNA editing levels are commonly genetically regulated (editing quantitative trait loci, edQTLs) consistently across development or predominantly during prenatal or postnatal periods. Both consistent and temporal-predominant edQTLs co-localize with risk loci associated with neurological traits and disorders, including attention deficit hyperactivity disorder, schizophrenia, and sleep disorders. These findings expand the repertoire of highly regulated RNA editing sites in the brain and provide insights of how epitranscriptional sequence diversity by RNA editing contributes to neurodevelopment.
BRN2 and PTN unveil multiple neurodevelopmental mechanisms in Schizophrenia patient-derived cerebral organoids
Authors: Notaras Michael , Lodhi Aiman , Dundar Friederike , Collier Paul , Sayles Nicole , Tilgner Hagen , Greening David , Colak Dilek 
Published: June 2021

ABSTRACTDue to an inability to ethically access developing human brain tissue as well as identify prospective cases, early-arising neurodevelopmental and cell-specific signatures of Schizophrenia (Scz) have remained unknown and thus undefined. To overcome these challenges, we utilized Scz patient-derived stem cells to generate 3D cerebral organoids to model neuropathology of Scz during this critical period. We discovered that Scz organoids exhibited ventricular neuropathology resulting in altered progenitor survival and disrupted neurogenesis. This ultimately yielded fewer neurons within developing cortical fields of Scz organoids. Single-cell sequencing revealed that Scz progenitors were specifically depleted of neuronal programming factors leading to a remodeling of cell-lineages, altered differentiation trajectories, and distorted cortical cell-type diversity. While Scz organoids were 99.95% similar in their macromolecular diversity to Ctrls, four GWAS factors (PTN, COMT, PLCL1, and PODXL) and peptide fragments belonging to the POU-domain transcription factor family (e.g. POU3F2/BRN2) were altered. This revealed that Scz organoids principally differed not in their proteomic diversity, but specifically in their total quantity of disease and neurodevelopmental factors at the molecular level. Single-cell sequencing also subsequently identified cell-type specific alterations in neuronal programming factors and growth factors, and specifically replicated the depletion of POU3F2 (BRN2) and PTN in both Scz progenitors and neurons. Consequently, in two mechanistic rescue experiments we identified that the transcription factor POU3F2 (BRN2) and growth factor PTN operate as mechanistic substrates of neurogenesis and cellular survival, respectively, in Scz organoids. This suggests that multiple mechanisms of Scz exist in patient-derived organoids, and that these disparate mechanisms converge upon primordial brain developmental pathways such as neuronal differentiation, survival, and growth factor support, which may amalgamate to elevate intrinsic risk of Scz.
MPI8 is Potent Against SARS-CoV-2 by Inhibiting Dually and Selectively the SARS-CoV-2 Main Protease and the Host Cathepsin L
Authors: Ma Xinyu R. , Alugubelli Yugendar R. , Ma Yuying , Vantasever Erol C. , Scott Danielle A. , Qiao Yuchen , Yu Ge , Xu Shiqing , Liu Wenshe Ray 
Published: June 2021

ABSTRACTA number of inhibitors have been developed for the SARS-CoV-2 main protease (MPro) as potential COVID-19 medications but little is known about their selectivity. Using enzymatic assays, we characterized inhibition of TMPRSS2, furin, and cathepsins B/K/L by more than a dozen of previously developed MPro inhibitors including MPI1-9, GC376, 11a, 10-1, 10-2, and 10- 3. MPI1-9, GC376 and 11a all contain an aldehyde for the formation of a reversible covalent hemiacetal adduct with the MPro active site cysteine and 10-1, 10-2 and 10-3 contain a labile ester to exchange with the MPro active site cysteine for the formation of a thioester. Our data revealed that all these inhibitors are inert toward TMPRSS2 and furin. Diaryl esters also showed low inhibition of cathepsins. However, all aldehyde inhibitors displayed high potency in inhibiting three cathepsins. Their determined IC50 values vary from 4.1 to 380 nM for cathepsin B, 0.079 to 2.3 nM for cathepsin L, and 0.35 to 180 nM for cathepsin K. All aldehyde inhibitors showed similar inhibition levels toward cathepsin L. A cellular analysis indicated high potency of MPI5 and MPI8 in inhibiting lysosomal activity, which is probably attributed to their inhibition of cathepsins. Among all aldehyde inhibitors, MPI8 shows the best selectivity toward cathepsin L. With respect to cathepsins B and K, the selective indices are 192 and 150, respectively. MPI8 is the most potent compound among all aldehyde inhibitors in cellular MPro inhibition potency and anti-SARS-CoV-2 activity in Vero E6 cells. Cathepsin L has been demonstrated to play a critical role in the SARS-CoV-2 cell entry. By selectively inhibiting both SARS-CoV-2 MPro and the host cathepsin L, MPI8 potentiates dual inhibition effects to synergize its overall antiviral potency and efficacy. Due to its high selectivity toward cathepsin L that reduces potential toxicity toward host cells and high cellular and antiviral potency, we urge serious consideration of MPI8 for preclinical and clinical investigations for treating COVID-19.
A midbody component homolog, too much information/prc1-like, is required for microtubule reorganization during both cytokinesis and axis induction in the early zebrafish embryo
Authors: Nair S , Welch E.L. , Moravec C.E. , Trevena R.L. , Pelegri F. 
Published: June 2021

AbstractWe show that the zebrafish maternal-effect mutation too much information (tmi) corresponds to zebrafish prc1-like (prc1l), which encodes a member of the MAP65/Ase1/PRC1family of microtubule-associated proteins. Embryos from tmi/prc1l homozygous mutant mothers display cytokinesis defects in meiotic and mitotic divisions in the early embryo, indicating that tmi/prc1l has a role in midbody formation during cell division at the egg-to-embryo transition. Unexpectedly, maternal tmi/prc1l function is also essential for the reorganization of vegetal pole microtubules required for embryonic axis induction. While Prc1 is widely regarded to crosslink microtubules in an antiparallel conformation, our studies provide evidence for an additional function of Prc1 in the bundling of parallel microtubules in the vegetal cortex of the early embryo during cortical rotation and prior to mitotic cycling. These findings highlight common yet distinct aspects of microtubule reorganization that occur during the egg-to-embryo transition, driven by maternal product for the midbody component Prc1l and required for embryonic cell division and pattern formation.
Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells
Authors: Calandrelli Riccardo , Wen Xingzhao , Charles Richard John Lalith , Luo Zhifei , Nguyen Tri C. , Chen Chien-Ju , Qi Zhijie , Xue Shuanghong , Chen Weizhong , Yan Zhangming , Wu Weixin , Zaleta-Rivera Kathia , Hu Rong , Yu Miao , Wang Yuchuan , Li Wenbo , Ma Jian , Ren Bing , Zhong Sheng 
Published: June 2021

AbstractThe interphase genome is dynamically organized in the nucleus and decorated with chromatin-associated RNA (caRNA). It remains unclear whether the genome architecture modulates the spatial distribution of caRNA and vice versa. Here, we generate a resource of genome-wide RNA-DNA and DNA-DNA contact maps in human cells. These maps reveal the chromosomal domains demarcated by locally transcribed RNA, hereafter termed RNA-defined chromosomal domains. Further, the spreading of caRNA is constrained by the boundaries of topologically associating domains (TADs), demonstrating the role of the 3D genome structure in modulating the spatial distribution of RNA. Conversely, stopping transcription or acute depletion of RNA induces thousands of chromatin loops genome-wide. Activation or suppression of the transcription of specific genes suppresses or creates chromatin loops straddling these genes. Deletion of a specific caRNA-producing genomic sequence promotes chromatin loops that straddle the interchromosomal target sequences of this caRNA. These data suggest a feedback loop where the 3D genome modulates the spatial distribution of RNA, which in turn affects the dynamic 3D genome organization.
A Novel Local Ablation Approach for Explaining Multimodal Classifiers
Authors: Ellis Charles A. , Carbajal Darwin A. , Zhang Rongen , Sendi Mohammad S.E. , Miller Robyn L. , Calhoun Vince D. , Wang May D. 
Published: June 2021

ABSTRACTWith the growing use of multimodal data for deep learning classification in healthcare research, more studies have begun to present explainability methods for insight into multimodal classifiers. Among these studies, few have utilized local explainability methods, which could provide (1) insight into the classification of each sample and (2) an opportunity to better understand the effects of demographic and clinical variables within datasets (e.g., medication of subjects in electrophysiology data). To the best of our knowledge, this opportunity has not yet been explored within multimodal classification. We present a novel local ablation approach that shows the importance of each modality to the correct classification of each class and explore the effects of demographic and clinical variables upon the classifier. As a use-case, we train a convolutional neural network for automated sleep staging with electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) data. We find that EEG is the most important modality across most stages, though EOG is particular important for non-rapid eye movement stage 1. Further, we identify significant relationships between the local explanations and subject age, sex, and state of medication which suggest that the classifier learned specific features associated with these variables across multiple modalities and correctly classified samples. Our novel explainability approach has implications for many fields involving multimodal classification. Moreover, our examination of the degree to which demographic and clinical variables may affect classifiers could provide direction for future studies in automated biomarker discovery.
A putative de novo evolved gene required for spermatid chromatin condensation in Drosophila melanogaster
Authors: Rivard Emily L. , Ludwig Andrew G. , Patel Prajal H. , Grandchamp Anna , Arnold Sarah E. , Berger Alina , Scott Emilie M. , Kelly Brendan J. , Mascha Grace C. , Bornberg-Bauer Erich , Findlay Geoffrey D. 
Published: June 2021

AbstractComparative genomics has enabled the identification of genes that potentially evolved de novo from non-coding sequences. Many such genes are expressed in male reproductive tissues, but their functions remain poorly understood. To address this, we conducted a functional genetic screen of over 40 putative de novo genes with testis-enriched expression in Drosophila melanogaster and identified one gene, atlas, required for male fertility. Detailed genetic and cytological analyses showed that atlas is required for proper chromatin condensation during the final stages of spermatogenesis. Atlas protein is expressed in spermatid nuclei and facilitates the transition from histone- to protamine-based chromatin packaging. Complementary evolutionary analyses revealed the complex evolutionary history of atlas. The protein-coding portion of the gene likely arose at the base of the Drosophila genus on the X chromosome but was unlikely to be essential, as it was then lost in several independent lineages. Within the last ∼15 million years, however, the gene moved to an autosome, where it fused with a conserved non-coding RNA and evolved a non-redundant role in male fertility. Altogether, this study provides insight into the integration of novel genes into biological processes, the links between genomic innovation and functional evolution, and the genetic control of a fundamental developmental process, gametogenesis.Author SummaryGenomes are in flux, as genes are constantly added and lost throughout evolution. New genes were once thought to arise almost exclusively via the modification or duplication of existing genes. Recently, however, interest has grown in alternative modes of new gene origination, such as de novo evolution from genetic material that previously did not encode proteins. Many de novo genes are expressed in male reproductive tissues, but their significance for fertility is not well understood. We screened likely de novo genes expressed in the Drosophila testis for reproductive roles and found one gene, atlas, essential for male fertility. We leveraged genetic and cell biological experiments to investigate roles for Atlas protein in reproduction and found that it is required during sperm development for proper packaging of DNA in the sperm nucleus. Evolutionary analyses of this gene revealed a complicated history, including loss in some lineages, movement between chromosomes, and fusion with a non-protein-coding gene. Studying both the functions and evolutionary histories of new proteins illustrates how they might evolve critical roles in biological processes despite their relative novelty. Furthermore, the study of atlas identifies an essential genetic player in the fly testis, an important model system for understanding how gametes are produced.
Exploiting node metadata to predict interactions in large networks using graph embedding and neural networks
Authors: Runghen Rogini , Stouffer Daniel B , Dalla Riva Giulio V 
Published: June 2021

AbstractCollecting network interaction data is difficult. Non-exhaustive sampling and complex hidden processes often result in an incomplete data set. Thus, identifying potentially present but unobserved interactions is crucial both in understanding the structure of large scale data, and in predicting how previously unseen elements will interact. Recent studies in network analysis have shown that accounting for metadata (such as node attributes) can improve both our understanding of how nodes interact with one another, and the accuracy of link prediction. However, the dimension of the object we need to learn to predict interactions in a network grows quickly with the number of nodes. Therefore, it becomes computationally and conceptually challenging for large networks. Here, we present a new predictive procedure combining a graph embedding method with machine learning techniques to predict interactions on the base of nodes’ metadata. Graph embedding methods project the nodes of a network onto a—low dimensional—latent feature space. The position of the nodes in the latent feature space can then be used to predict interactions between nodes. Learning a mapping of the nodes’ metadata to their position in a latent feature space corresponds to a classic—and low dimensional—machine learning problem. In our current study we used the Random Dot Product Graph model to estimate the embedding of an observed network, and we tested different neural networks architectures to predict the position of nodes in the latent feature space. Flexible machine learning techniques to map the nodes onto their latent positions allow to account for multivariate and possibly complex nodes’ meta-data. To illustrate the utility of the proposed procedure, we apply it to a large dataset of tourist visits to destinations across New Zealand. We found that our procedure accurately predicts interactions for both existing nodes and nodes newly added to the network, while being computationally feasible even for very large networks. Overall, our study highlights that by exploiting the properties of a well understood statistical model for complex networks and combining it with standard machine learning techniques, we can simplify the link prediction problem when incorporating multivariate node metadata. Our procedure can be immediately applied to different types of networks, and to a wide variety of data from different systems. As such, both from a network science and data science perspective, our work offers a flexible and generalisable procedure for link prediction.
Mitochondrial COA7 is a heme-binding protein involved in the early stages of complex IV assembly
Authors: Formosa Luke E. , Maghool Shadi , Sharpe Alice J. , Reljic Boris , Muellner-Wong Linden , Stroud David A. , Ryan Michael T. , Maher Megan J. 
Published: June 2021

AbstractCytochrome c oxidase assembly factor 7 (COA7) is a metazoan-specific assembly factor, critical for the biogenesis of mitochondrial complex IV (cytochrome c oxidase). Although mutations in COA7 have been linked in patients to complex IV assembly defects and neurological conditions such as peripheral neuropathy, ataxia and leukoencephalopathy, the precise role COA7 plays in the biogenesis of complex IV is not known. Here we show that the absence of COA7 leads to arrest of the complex IV assembly pathway at the initial step where the COX1 module is built, which requires incorporation of copper and heme cofactors. In solution, purified COA7 binds heme with micromolar affinity, through axial ligation to the central iron atom by histidine and methionine residues. Surprisingly, the crystal structure of COA7, determined to 2.4 Å resolution, reveals a ‘banana-shaped’ molecule composed of five helix-turn-helix (α/α) repeats, tethered by disulfide bonds, with a structure entirely distinct from proteins with characterized heme binding activities. We therefore propose a role for COA7 in heme binding/chaperoning in the mitochondrial intermembrane space, this activity being crucial for and providing a missing link in complex IV biogenesis.Significance StatementAssembly factors play key roles in the biogenesis of many mitochondrial protein complexes regulating their stability, activity and incorporation of essential cofactors. COA7 is a metazoan-specific assembly factor, the absence or mutation of which in humans accompanies complex IV assembly defects and neurological conditions. Here we report the crystal structure of COA7 to 2.4 Å resolution, revealing a ‘banana-shaped’ molecule composed of five helix-turn-helix (α/α) repeats, tethered by disulfide bonds. Characterization of pathogenic variants reveals significantly lower stabilities, correlating with the associated disease outcomes. Fascinatingly, COA7 binds heme with micromolar affinity, despite the fact that the protein structure does not resemble previously characterized heme-binding proteins. This provides a possible missing link for heme handling in the mitochondrial intermembrane space.