bluuebunny/crossref_metadata_2025 huggingface dataset:
DPSleep: Open-Source Longitudinal Sleep Analysis From Accelerometer Data
Authors: Rahimi-Eichi Habiballah , Coombs Garth , Vidal Bustamante Constanza M. , Onnela Jukka-Pekka , Baker Justin T. , Buckner Randy L.
Published: February 2021

Wearable devices are now widely available to collect continuous objective behavioral data from individuals and to measure sleep. Here we introduce a pipeline to infer sleep onset, duration, and quality from raw accelerometer data and then quantify relationships between derived sleep metrics and other variables of interest. The pipeline released here for the deep phenotyping of sleep, as the “DPSleep” software package, uses (a) a stepwise algorithm to detect missing data; (b) within-individual, minute-based, spectral power percentiles of activity; and (c) iterative, forward- and backward-sliding windows to estimate the major Sleep Episode onset and offset. Software modules allow for manual quality control adjustment of derived sleep features and correction for time zone changes. In this report, we illustrate the pipeline with data from participants studied for more than 200 days each. Actigraphy-based measures of sleep duration are associated with self-report rating of sleep quality. Simultaneous measures of smartphone use and GPS location data support the validity of the sleep timing inferences and reveal how phone measures of sleep timing can differ from actigraphy data. We discuss the uses of DPSleep in relation to other available sleep estimation approaches and provide example use cases that include multi-dimensional, deep longitudinal phenotyping, extended measurement of dynamics associated with mental illness, and the possibility of combining wearable actigraphy and personal electronic device data (e.g., smartphone, tablet) to measure individual differences across a wide range of behavioral variation in health and disease.
The mutation profile of SARS-CoV-2 is primarily shaped by the host antiviral defense
Authors: Azgari Cem , Kilinc Zeynep , Turhan Berk , Circi Defne , Adebali Ogun
Published: February 2021

Understanding SARS-CoV-2 evolution is a fundamental effort in coping with the COVID-19 pandemic. The virus genomes have been broadly evolving due to the high number of infected hosts world-wide. Mutagenesis and selection are the two inter-dependent mechanisms of virus diversification. However, which mechanisms contribute to the mutation profiles of SARS-CoV-2 remain under-explored. Here, we delineate the contribution of mutagenesis and selection to the genome diversity of SARS-CoV-2 isolates. We generated a comprehensive phylogenetic tree with representative genomes. Instead of counting mutations relative to the reference genome, we identified each mutation event at the nodes of the phylogenetic tree. With this approach, we obtained the mutation events that are independent of each other and generated the mutation profile of SARS-CoV-2 genomes. The results suggest that the heterogeneous mutation patterns are mainly reflections of host (i) antiviral mechanisms that are achieved through APOBEC, ADAR, and ZAP proteins and (ii) probable adaptation against reactive oxygen species.

Importance

SARS-CoV-2 genomes are evolving worldwide. Revealing the evolutionary characteristics of SARS-CoV-2 is essential to understand host-virus interactions. Here, we aim to understand whether mutagenesis or selection is the primary driver of SARS-CoV-2 evolution. This study provides an unbiased computational method for profiling and analyzing independently occurring SARS-CoV-2 mutations. The results point out three host antiviral mechanisms shaping the mutational profile of SARS-CoV-2 through APOBEC, ADAR, and ZAP proteins. Besides, reactive oxygen species might have an impact on the SARS-CoV-2 mutagenesis.
14-3-3ζ-depletion impairs mammary gland development in the mouse
Authors: Poltavets Valentina , Esmaeili Zahra , Boyle Sarah T. , Ramshaw Hayley S. , Lopez Angel F. , Kochetkova Marina , Samuel Michael S.
Published: February 2021

The 14-3-3 family of proteins have roles in regulating several key cellular processes. While their significant structural and functional homology had informed the idea that these proteins acted redundantly, it is now becoming clear that individual family members may have tissue and context specific functions, highlighting the need for a more nuanced understanding of these important proteins. Here, we demonstrate that mice deficient in 14-3-3ζ exhibit developmental defects of the mammary epithelium, associated with dysregulation of key transcription factors involved in the maintenance of mammary stem cell populations. We believe that this model will be prove useful for investigating the role of 14-3-3ζ in the maintenance of mammary stem cell populations and elucidating the transcriptional networks driving specification of the mammary epithelium.
Tig1 regulates proximo-distal identity during salamander limb regeneration
Authors: Oliveira Catarina R. , Knapp Dunja , Elewa Ahmed , Gerber Tobias , Gonzalez Malagon Sandra G. , Gates Phillip B. , Walters Hannah E. , Petzold Andreas , Arce Hernan , Cordoba Rodrigo C. , Subramanian Elaiyaraja , Chara Osvaldo , Tanaka Elly M. , Simon András , Yun Maximina H.
Published: February 2021

Salamander limb regeneration is an accurate process which gives rise exclusively to the missing structures, irrespective of the amputation level. This suggests that cells in the stump have an awareness of their spatial location, a property termed ‘positional identity’. Little is known about how positional identity is encoded, in salamanders or other biological systems. Through single-cell RNAseq analysis, we identified Tig1/Rarres1 as a potential determinant of proximal identity. Tig1 encodes a conserved cell surface molecule, is regulated by retinoic acid and exhibits a graded expression along the proximo-distal axis of the limb. Its overexpression leads to regeneration defects in the distal elements and elicits proximal displacement of blastema cells, while its neutralisation blocks proximo-distal cell surface interactions. Critically, Tig1 reprogrammes distal cells to a proximal identity, upregulating Prod1 and inhibiting Hoxa13 and distal transcriptional networks. Thus, Tig1 is a central cell surface determinant of proximal identity in the salamander limb.
Allogeneic CAR-invariant Natural Killer T Cells Exert Potent Antitumor Effects Through Host CD8 T Cell Cross-Priming
Authors: Simonetta Federico , Lohmeyer Juliane K. , Hirai Toshihito , Maas-Bauer Kristina , Alvarez Maite , Wenokur Arielle S. , Baker Jeanette , Aalipour Amin , Ji Xuhuai , Haile Samuel , Mackall Crystal L. , Negrin Robert S.
Published: February 2021

The development of allogeneic chimeric antigen receptor (CAR) T cell therapies for off-the-shelf use is a major goal yet faces two main immunological challenges, namely the risk of graft-versus-host-disease (GvHD) induction by the transferred cells and the rejection by the host immune system limiting their persistence. We demonstrate that allogeneic CAR-engineered invariant natural killer T (iNKT) cells, a cell population without GvHD-induction potential that displays immunomodulatory properties, exerted potent direct and indirect antitumor activity in murine models of B-cell lymphoma when administered across major MHC-barriers. In addition to their known direct cytotoxic effect, allogeneic CAR iNKT cells induced tumor-specific antitumor immunity through host CD8 T cell cross-priming, resulting in a potent antitumor effect lasting longer than the physical persistence of the allogeneic cells. The utilization of off-the-shelf allogeneic CAR iNKT cells could meet significant unmet needs in the clinic.
A modular platform for engineering function of natural and synthetic biomolecular condensates
Authors: Lasker Keren , Boeynaems Steven , Lam Vinson , Stainton Emma , Jacquemyn Maarten , Daelemans Dirk , Villa Elizabeth , Holehouse Alex S. , Gitler Aaron D. , Shapiro Lucy
Published: February 2021

Phase separation is emerging as a universal principle for how cells use dynamic subcompartmentalization to organize biochemical reactions in time and space1,2. Yet, whether the emergent physical properties of these biomolecular condensates are important for their biological function remains unclear. The intrinsically disordered protein PopZ forms membraneless condensates at the poles of the bacteriumCaulobacter crescentusand selectively sequesters kinase-signaling cascades to regulate asymmetric cell division3–5. By dissecting the molecular grammar underlying PopZ phase separation, we find that unlike many eukaryotic examples, where unstructured regions drive condensation6,7, a structured domain of PopZ drives condensation, while conserved repulsive features of the disordered region modulate material properties. By generating rationally designed PopZ mutants, we find that the exact material properties of PopZ condensates directly determine cellular fitness, providing direct evidence for the physiological importance of the emergent properties of biomolecular condensates. Our work codifies a clear set of design principles illuminating how sequence variation in a disordered domain alters the function of a widely conserved bacterial condensate. We used these insights to repurpose PopZ as a modular platform for generating synthetic condensates of tunable function in human cells.
Impact of the B.1.1.7 variant on neutralizing monoclonal antibodies recognizing diverse epitopes on SARS-CoV-2 Spike
Authors: Graham Carl , Seow Jeffrey , Huettner Isabella , Khan Hataf , Kouphou Neophytos , Acors Sam , Winstone Helena , Pickering Suzanne , Galao Rui Pedro , Lista Maria Jose , Jimenez-Guardeno Jose M , Laing Adam G. , Wu Yin , Joseph Magdalene , Muir Luke , Ng Weng M. , Duyvesteyn Helen M. E. , Zhao Yuguang , Bowden Thomas A. , Shankar-Hari Manu , Rosa Annachiara , Cherepanov Peter , McCoy Laura E. , Hayday Adrian C. , Neil Stuart J.D. , Malim Michael H. , Doores Katie J.
Published: February 2021

The interaction of the SARS-CoV-2 Spike receptor binding domain (RBD) with the ACE2 receptor on host cells is essential for viral entry. RBD is the dominant target for neutralizing antibodies and several neutralizing epitopes on RBD have been molecularly characterized. Analysis of circulating SARS-CoV-2 variants has revealed mutations arising in the RBD, the N-terminal domain (NTD) and S2 subunits of Spike. To fully understand how these mutations affect the antigenicity of Spike, we have isolated and characterized neutralizing antibodies targeting epitopes beyond the already identified RBD epitopes. Using recombinant Spike as a sorting bait, we isolated >100 Spike-reactive monoclonal antibodies from SARS-CoV-2 infected individuals. ~45% showed neutralizing activity of which ~20% were NTD-specific. None of the S2-specific antibodies showed neutralizing activity. Competition ELISA revealed that NTD-specific mAbs formed two distinct groups: the first group was highly potent against infectious virus, whereas the second was less potent and displayed glycan-dependant neutralization activity. Importantly, mutations present in B.1.1.7 Spike frequently conferred resistance to neutralization by the NTD-specific neutralizing antibodies. This work demonstrates that neutralizing antibodies targeting subdominant epitopes need to be considered when investigating antigenic drift in emerging variants.
Summix:A method for detecting and adjusting for population structure in genetic summary data
Authors: Arriaga-MacKenzie IS , Matesi G , Chen S , Ronco A , Marker KM , Hall JR , Scherenberg R , Khajeh-Sharafabadi M , Wu Y , Gignoux CR , Null M , Hendricks AE
Published: February 2021

Publicly available genetic summary data have high utility in research and the clinic including prioritizing putative causal variants, polygenic scoring, and leveraging common controls. However, summarizing individual-level data can mask population structure resulting in confounding, reduced power, and incorrect prioritization of putative causal variants. This limits the utility of publicly available data, especially for understudied or admixed populations where additional research and resources are most needed. While several methods exist to estimate ancestry in individual-level data, methods to estimate ancestry proportions in summary data are lacking. Here, we present Summix, a method to efficiently deconvolute ancestry and provide ancestry-adjusted allele frequencies from summary data. Using continental reference ancestry, African (AFR), Non-Finnish European (EUR), East Asian (EAS), Indigenous American (IAM), South Asian (SAS), we obtain accurate and precise estimates (within 0.1%) for all simulation scenarios. We apply Summix to gnomAD v2.1 exome and genome groups and subgroups finding heterogeneous continental ancestry for several groups including African/African American (∼84% AFR, ∼14% EUR) and American/Latinx (∼4% AFR, ∼5% EAS, ∼43% EUR, ∼46% IAM). Compared to the unadjusted gnomAD AFs, Summix’s ancestry-adjusted AFs more closely match respective African and Latinx reference samples. Even on modern, dense panels of summary statistics, Summix yields results in seconds allowing for estimation of confidence intervals via block bootstrap. Given an accompanying R package, Summix increases the utility and equity of public genetic resources, empowering novel research opportunities.
Molecular dynamics simulation study reveals effects of key mutations on spike protein structure in SARS-CoV-2
Authors: Lon Jerome Rumdon , Xi Binbin , Zhong Bingxu , Zheng Yiyuan , Chen Zixi , Qiu Ruoran , Zhang Siqing , Guo Pei , Du Hongli
Published: February 2021

SARS-CoV-2 has been spreading rapidly since 2019 and has produced large-scale mutations in the genomes. The mutation in genes may lead to changes in protein structure, which would have a great impact on the epidemiological characteristics. In this study, we selected the key mutations of SARS-CoV-2 from a real-time monitoring tool, including D614G, A222V, N501Y, T716I, S982A, D1118H of spike (S) protein, and performed molecular dynamics (MD) simulations on single-site mutant D614G, double-site mutant D614G&A222V and penta-site mutant N501Y&D614G&T716I&S982A&D1118H to investigate their effects on protein structure and stability using molecular dynamics (MD) simulations. The results suggested that D614G improved the stability of S protein, while D614G&A222V and N501Y&D614G&T716I&S982A&D1118H showed an increased solvent accessible surface area and they might enhance the ability of protein to react with the outside environment. Our findings could complement the mechanistic link between genotype--phenotype--epidemiological characteristics in the study of SARS-CoV-2. We also found no significant difference between the antigenicity of S protein and the mutants through Ellipro, which may reference for vaccine development and application.
Bridging Between Material Properties Of Proteins And The Underlying Molecular Interactions
Authors: Song Guang
Published: February 2021

In this work, we develop a novel method that bridges between material properties of proteins, particularly the modulus of elasticity, and the underlying molecular interactions. To this end, we employ both an all-atom normal mode analysis (NMA) model with the CHARMM force field and an elastic solid model for proteins and protein interfaces. And the “bridge” between the two models is a common physical property that they both can predict: the magnitude of thermal vibrations. This connection allows one to calibrate the Young’s moduli of proteins and protein interface regions. We find that the elastic moduli of proteins are mostly in the range of a few Gpa to 10 Gpa, while the elastic moduli of the interface regions are about an order smaller. The work is significant as it represents the first attempt to systematically compute the moduli of elasticity of proteins from molecular interactions.
SamQL: A Structured Query Language and filtering tool for the SAM/BAM file format
Authors: Lee Christopher T , Maragkakis Manolis
Published: February 2021

The Sequence Alignment/Map Format Specification (SAM) is one of the most widely used file formats in computational biology today and several tools have been developed to process it and use it. It is a flexible file format, used by many bioinformaticians on a daily basis. Despite its flexibility, SAM encoded files can often be difficult to query and understand. As genomic data are rapidly growing, structured and efficient queries on data encoded in SAM/BAM files is becoming critical. Importantly, any new tools should be able to support existing large datasets without requiring any data transformations. Here we introduce SamQL, an SQL-like query language for the SAM format with intuitive syntax that supports complex and efficient queries on top of SAM/BAM files and that can replace commonly used Bash one-liners employed by many bioinformaticians. SamQL is a complete query language that we envision as a step to a structured database engine for genomics. SamQL is written in Go, taking advantage of modern multicore compute systems and is freely available as standalone program and as an open-source library released under an MIT license,https://github.com/maragkakislab/samql/.
Inferring time-lagged causality using the derivative of single-cell expression
Authors: Wei Huan-Huan , Lu Hui , Zhao Hongyu
Published: February 2021

Many computational methods have been developed for inferring causality among genes using cross-sectional gene expression data, such as single-cell RNA sequencing (scRNA-seq) data. However, due to the limitations of scRNA-seq technologies, time-lagged causal relationships may be missed by existing methods. In this work, we propose a method, called causal inference with time-lagged information (CITL), to infer time-lagged causal relationships from scRNA-seq data by assessing conditional independence between the changing and current expression levels of genes. CITL estimates the changing expression levels of genes by “RNA velocity”. We demonstrate the accuracy and stability of CITL for inferring time-lagged causality on simulation data against other leading approaches. We have applied CITL to real scRNA data and inferred 878 pairs of time-lagged causal relationships, with many of these inferred results supported by the literature.

Author summary

Computational causal inference is a promising way to survey causal relationships between genes efficiently. Though many causal inference methods have been applied to gene expression data, none considers the time-lagged causal relationship, which means that some genes may take some time to affect their target genes with several reactions. If relationships between genes are time-lagged, the existing methods’ assumptions will be violated. The relationships will be challenging to recognize. We demonstrate that this is indeed the case through simulation. Therefore, we develop a method for inferring time-lagged causal relationships of single-cell gene expression data. We assume that a time-lagged causal relationship should present a strong association between the cause and the effect’s changing. To calculate such correlation, we first estimate the derivative of gene expression using the information from unspliced transcripts. Then, we use conditional independent tests to search gene pairs satisfying our assumption. Our results suggest that we could accurately infer time-lagged causal gene pairs validated by published literature. This method may complement gene regulatory analysis and provide candidate gene pairs for further controlled experiments.
Selection of stimulus parameters for enhancing slow wave sleep events with a Neural-field theory thalamocortical computational model
Authors: Torres Felipe A. , Orio Patricio , Escobar María-José
Published: February 2021

Slow-wave sleep cortical brain activity, conformed by slow-oscillations and sleep spindles, plays a key role in memory consolidation. The increase of the power of the slow-wave events, obtained by auditory sensory stimulation, positively correlates to memory consolidation performance. However, little is known about the experimental protocol maximizing this effect, which could be induced by the power of slow-oscillation, the number of sleep spindles, or the timing of both events’ co-occurrence. Using a mean-field model of thalamocortical activity, we studied the effect of several stimulation protocols, varying the pulse shape, duration, amplitude, and frequency, as well as a target-phase using a closed-loop approach. We evaluated the effect of these parameters on slow-oscillations (SO) and sleep-spindles (SP), considering: (i) the power at the frequency bands of interest, (ii) the number of SO and SP, (iii) co-occurrences between SO and SP, and (iv) synchronization of SP with the up-peak of the SO. The first three targets are maximized using a decreasing ramp pulse with a pulse duration of 50 ms. Also, we observed a reduction in the number of SO when increasing the stimulus energy by rising its amplitude. To assess the target-phase parameter, we applied closed-loop stimulation at 0º, 45º, and 90º of the phase of the narrow-band filtered ongoing activity, at 0.85 Hz as central frequency. The 0º stimulation produces better results in the power and number of SO and SP than the rhythmic or aleatory stimulation. On the other hand, stimulating at 45º or 90º change the timing distribution of spindles centers but with fewer co-occurrences than rhythmic and 0º phase. Finally, we propose the application of closed-loop stimulation at the rising zero-cross point using pulses with a decreasing ramp shape and 50 ms of duration for future experimental work.

Author summary

During the non-REM (NREM) phase of sleep, events that are known as slow oscillations (SO) and spindles (SP) can be detected by EEG. These events have been associated with the consolidation of declarative memories and learning. Thus, there is an ongoing interest in promoting them during sleep by non-invasive manipulations such as sensory stimulation. In this paper, we used a computational model of brain activity that generates SO and SP, to investigate which type of sensory stimulus –shape, amplitude, duration, periodicity– would be optimal for increasing the events’ frequency and their co-occurrence. We found that a decreasing ramp of 50 ms duration is the most effective. The effectiveness increases when the stimulus pulse is delivered in a closed-loop configuration triggering the pulse at a target phase of the ongoing SO activity. A desirable secondary effect is to promote SPs at the rising phase of the SO oscillation.
Variation in predicted COVID-19 risk among lemurs and lorises
Authors: Melin Amanda D. , Orkin Joseph D. , Janiak Mareike C. , Valenzuela Alejandro , Kuderna Lukas , Marrone Frank , Ramangason Hasinala , Horvath Julie E. , Roos Christian , Kitchener Andrew C. , Khor Chiea Chuen , Lim Weng Khong , Lee Jessica G. H. , Tan Patrick , Umapathy Govindhaswamy , Raveendran Muthuswamy , Harris R. Alan , Gut Ivo , Gut Marta , Lizano Esther , Nadler Tilo , Zinner Dietmar , Johnson Steig E. , Jarvis Erich D. , Fedrigo Olivier , Wu Dongdong , Zhang Guojie , Farh Kyle Kai-How , Rogers Jeffrey , Marques-Bonet Tomas , Navarro Arcadi , Juan David , Arora Paramjit S. , Higham James P.
Published: February 2021

The novel coronavirus SARS-CoV-2, which in humans leads to the disease COVID-19, has caused global disruption and more than 1.5 million fatalities since it first emerged in late 2019. As we write, infection rates are currently at their highest point globally and are rising extremely rapidly in some areas due to more infectious variants. The primary viral target is the cellular receptor angiotensin-converting enzyme-2 (ACE2). Recent sequence analyses of theACE2gene predicts that many nonhuman primates are also likely to be highly susceptible to infection. However, the anticipated risk is not equal across the Order. Furthermore, some taxonomic groups show high ACE2 amino acid conservation, while others exhibit high variability at this locus. As an example of the latter, analyses of strepsirrhine primateACE2sequences to date indicate large variation among lemurs and lorises compared to other primate clades despite low sampling effort. Here, we reportACE2gene and protein sequences for 71 individual strepsirrhines, spanning 51 species and 19 genera. Our study reinforces previous results and finds additional variability in other strepsirrhine species, and suggests several clades of lemurs have high potential susceptibility to SARS-CoV-2 infection. Troublingly, some species, including the rare and Endangered aye-aye (Daubentonia madagascariensis), as well as those in the generaAvahiandPropithecus, may be at high risk. Given that lemurs are endemic to Madagascar and among the primates at highest risk of extinction globally, further understanding of the potential threat of COVID-19 to their health should be a conservation priority. All feasible actions should be taken to limit their exposure to SARS-CoV-2.
Using population-specific add-on polymorphisms to improve genotype imputation in underrepresented populations
Authors: Xu Zhi Ming , Rüeger Sina , Zwyer Michaela , Brites Daniela , Hiza Hellen , Reinhard Miriam , Borrell Sonia , Isihaka Faima , Temba Hosiana , Maroa Thomas , Naftari Rastard , Hella Jerry , Sasamalo Mohamed , Reither Klaus , Portevin Damien , Gagneux Sebastien , Fellay Jacques
Published: February 2021

Genome-wide association studies rely on the statistical inference of untyped variants, called imputation, to increase the coverage of genotyping arrays. However, the results are often suboptimal in populations underrepresented in existing reference panels and array designs, since the selected single nucleotide polymorphisms (SNPs) may fail to capture population-specific haplotype structures, hence the full extent of common genetic variation. Here, we propose to sequence the full genome of a small subset of an underrepresented study cohort to inform the selection of population-specific add-on SNPs, such that the remaining array-genotyped cohort could be more accurately imputed. Using a Tanzania-based cohort as a proof-of-concept, we demonstrate the validity of our approach by showing improvements in imputation accuracy after the addition of our designed addon SNPs to the base H3Africa array.
RAD51 nuclear recruitment and inhibition towards innovative strategies against pancreatic cancer
Authors: Schipani Fabrizio , Manerba Marcella , Marotta Roberto , Gennari Arianna , Rinaldi Francesco , Armirotti Andrea , Roberti Marinella , Di Stefano Giuseppina , Rocchia Walter , Tirelli Nicola , Girotto Stefania , Cavalli Andrea
Published: February 2021

RAD51, a key player in the homologous recombination (HR) mechanism, is a critical protein to preserve genomic stability. BRCA2, upon DNA damage, promotes RAD51 fibrils disassembly and its nuclear recruitment.

Here, we use BRC4, a peptide derived from the fourth BRC repeat of BRCA2; BRC4 induces RAD51 defibrillation through a ‘domino’ effect, eroding fibrils from their termini, and yielding monomeric RAD51. The congruence among several techniques (static and dynamic light scattering, negative staining transmission electron microscopy (TEM), and microscale thermophoresis) allows an accurate estimation of the kinetic and thermodynamic parameters of this process. BRC4 lacks, however, a nuclear localization sequence; therefore, it cannot transport RAD51 into the nucleus, thus behaving as a RAD51 inhibitor. Cellular assays (BxPC-3, pancreatic cancer cells) indeed show that BRC4 efficiently inhibits HR and enhances the cytotoxic effect of cisplatin, a DNA-damaging drug.

The present study sheds further light on the complexity of the HR pathway, paving the way for designing peptide and small organic molecule inhibitors of RAD51 as innovative anticancer and chemo/radiosensitizer compounds.
SplicingFactory – Splicing diversity analysis for transcriptome data
Authors: Dankó Benedek , Szikora Péter , Pór Tamás , Szeifert Alexa , Sebestyén Endre
Published: February 2021

Motivation

Alternative splicing contributes to the diversity of RNA found in biological samples. Current tools investigating patterns of alternative splicing check for coordinated changes in the expression or relative ratio of RNA isoforms where specific isoforms are up- or downregulated in a condition. However, the molecular process of splicing is stochastic and changes in RNA isoform diversity for a gene might arise between samples or conditions. A specific condition can be dominated by a single isoform, while multiple isoforms with similar expression levels can be present in a different condition. These changes might be the result of mutations, drug treatments or differences in the cellular or tissue environment. Here, we present a tool for the characterization and analysis of RNA isoform diversity using isoform level expression measurements.

Results

We developed an R package called SplicingFactory, to calculate various RNA isoform diversity metrics, and compare them across conditions. Using the package, we tested the effect of RNA-seq quantification tools, quantification uncertainty, gene expression levels, and isoform numbers on the isoform diversity calculation. We analyzed a set of CD34+ hematopoietic stem cells and myelodysplastic syndrome samples and found a set of genes whose isoform diversity change is associated withSF3B1mutations.

Availability and implementation

The SplicingFactory package is freely available under the GPL-3.0 license from Bioconductor for the Windows, MacOS and Linux operating systems (https://www.bioconductor.org/packages/release/bioc/html/SplicingFactory.html).

Contact

sebestyen.endre@med.semmelweis-univ.hu

Supplementary information

Supplementary data are available at Bioinformatics online.
Mechanically induced localization of SECONDARY WALL INTERACTING bZIP is associated with thigmomorphogenic and secondary cell wall gene expression
Authors: Coomey Joshua H. , MacKinnon Kirk J.-M. , McCahill Ian W. , Khahani Bahman , Handakumbura Pubudu P. , Trabucco Gina M. , Mazzola Jessica , Leblanc Nicole A. , Kheam Rithany , Hernandez-Romero Miriam , Barry Kerrie , Liu Lifeng , Lee Ji E. , Vogel John P. , O’Malley Ronan C. , Chambers James J. , Hazen Samuel P.
Published: February 2021

Abstract

Plant growth requires the integration of internal and external cues, perceived and transduced into a developmental program of cell division, elongation, and wall thickening. Mechanical forces contribute to this regulation, and thigmomorphogenesis typically includes reducing stem height, increasing stem diameter, and a canonical transcriptomic response. We present data on a bZIP transcription factor involved in this process in grasses.Brachypodium distachyonSECONDARY WALL INTERACTING bZIP (SWIZ) protein translocated into the nucleus following mechanostimulation. Classical touch responsive genes were upregulated inB. distachyonroots following touch, including significant induction of the glycoside hydrolase 17 family, which may be unique to grass thigmomorphogenesis. SWIZ protein binding to an E-box variant in exons and introns was associated with immediate activation followed by repression of gene expression.SWIZoverexpression resulted in plants with reduced stem and root elongation. These data further define plant touch-responsive transcriptomics and physiology, offering insights to grass mechanotranduction dynamics.
S-acylation targets ORAI1 channels to lipid rafts for efficient Ca2+ signaling by T cell receptors at the immune synapse
Authors: Carreras-Sureda Amado , Abrami Laurence , Kim Ji-Hee , Frieden Maud , Didier Monica , Van der Goot F. Gisou , Demaurex Nicolas
Published: February 2021

Efficient immune responses require Ca2+ fluxes across ORAI1 channels during engagement of T cell receptors (TCR) at the immune synapse (IS) between T cells and antigen presenting cells. Here, we show that ZDHHC20-mediated S-acylation of the ORAI1 channel at residue Cys143 is required for TCR assembly and signaling at the IS. Cys143 mutations reduced ORAI1 currents and store-operated Ca2+ entry in HEK-293 cells and nearly abrogated long-lasting Ca2+ elevations, NFATC1 translocation, and IL-2 secretion evoked by TCR engagement in Jurkat T cells. The acylation-deficient channel had reduced mobility in lipids, accumulated in cholesterol-poor domains, formed tiny clusters, failed to reach the IS and unexpectedly also prevented TCR recruitment to the IS. Our results establish S-acylation as a critical regulator of ORAI1 channel assembly and function at the IS and reveal that local Ca2+ fluxes are required for TCR recruitment to the synapse.
Individuals at risk for developing rheumatoid arthritis harbor differential intestinal bacteriophage communities with distinct metabolic potential
Authors: Mangalea Mihnea R. , Paez-Espino David , Kieft Kristopher , Chatterjee Anushila , Seifert Jennifer A. , Feser Marie L. , Demoruelle M. Kristen , Chriswell Meagan E. , Sakatos Alexandra , Anantharaman Karthik , Deane Kevin D. , Kuhn Kristine A. , Holers V. Michael , Duerkop Breck A.
Published: February 2021

Rheumatoid arthritis (RA) is an autoimmune disease characterized in seropositive individuals by the presence of anti-cyclic citrullinated protein (CCP) antibodies. RA is linked to the intestinal microbiota, yet the association of microbes with CCP serology and their contribution to RA is unclear. We describe intestinal phage communities of individuals at risk for developing RA, with or without anti-CCP antibodies, whose first degree relatives have been diagnosed with RA. We show that at-risk individuals harbor intestinal phage compositions that diverge based on CCP serology, are dominated by Lachnospiraceae phages, and originate from disparate ecosystems. These phages encode unique repertoires of auxiliary metabolic genes (AMGs) which associate with anti-CCP status, suggesting that these phages directly influence the metabolic and immunomodulatory capability of the microbiota. This work sets the stage for the use of phages as preclinical biomarkers and provides insight into a possible microbial-based causation of RA disease development.
Does colour impact attention towards 2D images in geckos?
Authors: Katlein Nathan , Ray Miranda , Wilkinson Anna , Claude Julien , Kiskowski Maria , Wang Bin , Glaberman Scott , Chiari Ylenia
Published: February 2021

Animals are exposed to different visual stimuli that influence how they perceive and interact with their environment. Visual information such as shape and colour can help the animal detect, discriminate and make appropriate behavioural decisions for mate selection, communication, camouflage, and foraging. In all major vertebrate groups, it has been shown that certain species can discriminate and prefer certain colours and that colours may increase the response to a stimulus. However, because colour is often studied together with other potentially confounding factors, it is still unclear to what extent colour discrimination plays a crucial role in the perception of and attention towards biologically relevant and irrelevant stimuli. To address these questions in reptiles, we assessed the response of three gecko speciesCorrelophus ciliatus, Eublepharis macularius, andPhelsuma laticaudato familiar and novel 2D images in colour or grayscale. We found that while all species responded more often to the novel than to the familiar images, colour information did not influence object discrimination. We also found that the duration of interaction with images was significantly longer for the diurnal species,P. laticauda, than for the two nocturnal species, but this was independent from colouration. Finally, no differences among sexes were observed within or across species. Our results indicate that geckos discriminate between 2D images of different content independent of colouration, suggesting that colouration does not increase detectability or intensity of the response. These results are essential for uncovering which visual stimuli produce a response in animals and furthering our understanding of how animals use colouration and colour vision.
Photosynthesis dynamics and regulation sensed in the frequency domain
Authors: Nedbal Ladislav , Lazár Dušan
Published: February 2021

Foundations of photosynthesis research have been established mainly by studying the response of plants to changing light, typically to sudden exposure to a constant light intensity after a dark acclimation or light flashes. This approach remains valid and powerful, but can be limited by requiring dark acclimation before time-domain measurements and often assumes that rate constants determining the photosynthetic response do not change between the dark- and light-acclimation.

We present experimental data and mathematical models demonstrating that these limits can be overcome by measuring plant responses to sinusoidally modulated light of varying frequency. By its nature, such frequency-domain characterization is performed in light-acclimated plants with no need for prior dark acclimation. Amplitudes, phase shifts, and upper harmonic modulation extracted from the data for a wide range of frequencies can target different kinetic domains and regulatory feedbacks. The occurrence of upper harmonic modulation reflects non-linear phenomena, including photosynthetic regulation. To support these claims, we present a frequency- and time-domain response in chlorophyll fluorescence emission of the green algaChlorella sorokinianain the frequency range 1000 – 0.001 Hz. Based on these experimental data and numerical as well as analytical mathematical models, we propose that frequency-domain measurements can become a versatile new tool in plant sensing.

One sentence summary

It is proposed to characterize photosynthesis in the frequency domain without the need for dark adaptation and, thus, without assumptions about the dark-to-light transition.
Extending the Near Infrared Emission Range of Indium Phosphide Quantum Dots for MultiplexedIn VivoImaging
Authors: Saeboe Alexander M. , Nikiforov Alexey Y. , Toufanian Reyhaneh , Kays Joshua C. , Chern Margaret , Casas J. Paolo , Han Keyi , Piryatinski Andrei , Jones Dennis , Dennis Allison M.
Published: February 2021

This report of the reddest emitting indium phosphide quantum dots (InP QDs) to date demonstrates tunable, near infrared (NIR) photoluminescence and fluorescence multiplexing in the first optical tissue window with a material that avoids toxic constituents. This synthesis overcomes the InP synthesis “growth bottleneck” and extends the emission peak of InP QDs deeper into the first optical tissue window using an inverted QD heterostructure. The ZnSe/InP/ZnS core/shell/shell structure is designed to produce emission from excitons with heavy holes confined in InP shells wrapped around larger-bandgap ZnSe cores and protected by a second shell of ZnS. The InP QDs exhibit InP shell thickness-dependent tunable emission with peaks ranging from 515 – 845 nm. The high absorptivity of InP leads to effective absorbance and photoexcitation of the QDs with UV, visible, and NIR wavelengths in particles with diameters of eight nanometers or less. These nanoparticles extend the range of tunable direct-bandgap emission from InP-based nanostructures, effectively overcoming a synthetic barrier that has prevented InP-based QDs from reaching their full potential as NIR imaging agents. Multiplexed lymph node imaging in a mouse model shows the potential of the NIR-emitting InP particles forin vivoimaging.
The biochemical resolving power of fluorescence lifetime imaging: untangling the roles of the instrument response function and photon-statistics
Authors: Trinh Andrew L. , Esposito Alessandro
Published: February 2021

A deeper understanding of spatial resolution has led to innovations in microscopy and the disruption of biomedical research, as with super-resolution microscopy. To foster similar advances in time-resolved and spectral imaging, we have previously introduced the concept of ‘biochemical resolving power’ in fluorescence microscopy. Here, we apply those concepts to investigate how the instrument response function (IRF), sampling conditions, and photon-statistics limit the biochemical resolution of fluorescence lifetime microscopy. Using Fisher information analysis and Monte Carlo simulations, we reveal the complex dependencies between photon-statistics and the IRF, permitting us to quantify resolution limits that have been poorly understood (e.g., the minimum resolvable decay time for a given width of the IRF and photon-statistics) or previously underappreciated (e.g., optimization of the IRF for biochemical detection). With this work, we unravel common misunderstandings on the role of the IRF and provide theoretical insights with significant practical implications on the design and use of time-resolved instrumentation.
REHE: Fast Variance Components Estimation for Linear Mixed Models
Authors: Yue Kun , Ma Jing , Thornton Timothy , Shojaie Ali
Published: February 2021

Abstract

Linear mixed models are widely used in ecological and biological applications, especially in genetic studies. Reliable estimation of variance components is crucial for using linear mixed models. However, standard methods, such as the restricted maximum likelihood (REML), are computationally inefficient and may be unstable with small samples. Other commonly used methods, such as the Haseman-Elston (HE) regression, may yield negative estimates of variances. Utilizing regularized estimation strategies, we propose the restricted Haseman-Elston (REHE) regression and REHE with resampling (reREHE) estimators, along with an inference framework for REHE, as fast and robust alternatives that provide non-negative estimates with comparable accuracy to REML. The merits of REHE are illustrated using real data and benchmark simulation studies.
Microbial populations are shaped by dispersal and recombination in a low biomass subseafloor habitat
Authors: Anderson Rika E. , Graham Elaina D. , Huber Julie A. , Tully Benjamin J.
Published: February 2021

The subseafloor is a vast habitat that supports microorganisms that have a global scale impact on geochemical cycles. Many of the endemic microbial communities inhabiting the subseafloor consist of small populations under growth-limited conditions. For small populations, stochastic evolutionary events can have large impacts on intraspecific population dynamics and allele frequencies. These conditions are fundamentally different from those experienced by most microorganisms in surface environments, and it is unknown how small population sizes and growth-limiting conditions influence evolution and population structure in the subsurface. Using a two-year, high-resolution environmental time-series, we examine the dynamics of microbial populations from cold, oxic crustal fluids collected from the subseafloor site North Pond, located near the mid-Atlantic ridge. Our results reveal rapid shifts in overall abundance, allele frequency, and strain abundance across the time points observed, with evidence for homologous recombination between coexisting lineages. We show that the subseafloor aquifer is a dynamic habitat that hosts microbial metapopulations that disperse frequently through the crustal fluids, enabling gene flow and recombination between microbial populations. The dynamism and stochasticity of microbial population dynamics in North Pond suggests that these forces are important drivers in the evolution of microbial populations in the vast subseafloor habitat.

Significance Statement

The cold, oxic subseafloor is an understudied habitat that is difficult to access, yet important to global biogeochemical cycles and starkly different compared to microbial habitats on the surface of the Earth. Our understanding of microbial evolution and population dynamics is largely molded by studies of microbes living in surface habitats that can host 10-1,000 times more microbial biomass than is frequently observed in the subsurface. This study provides an opportunity to observe population dynamics within a low biomass, growth-limited environment and reveals that microbial populations in the subseafloor are influenced by changes in selection pressure and gene sweeps. In addition, recombination between strains that have dispersed from elsewhere within the aquifer has an important impact on the evolution of microbial populations. Much of the microbial life on the planet exists under growth-limited conditions and the subseafloor provides a natural laboratory to explore how life evolves in such environments.
Mutation of lipoprotein processing pathway genelspAor inhibition of LspA activity by globomycin increases MRSA resistance to β-lactam antibiotics
Authors: Fingleton Claire , Zeden Merve S. , Bueno Emilio , Cava Felipe , O’Gara James P.
Published: February 2021

TheStaphylococcus aureuscell envelope comprises numerous components, including peptidoglycan (PG), wall teichoic acids (WTA), lipoteichoic acids (LTA), targeted by antimicrobial drugs. MRSA resistance to methicillin is mediated by themecA-encoded β-lactam-resistant transpeptidase, penicillin binding protein 2a (PBP2a). However, PBP2a-dependent β-lactam resistance is also modulated by the activity of pathways involved in the regulation or biosynthesis of PG, WTA or LTA. Here, we report that mutation of the lipoprotein signal peptidase II gene,lspA, from the lipoprotein processing pathway, significantly increased β-lactam resistance in MRSA. Mutation oflgt, which encodes diacylglycerol transferase (Lgt) responsible for synthesis of the LspA substrate did not impact β-lactam susceptibility. Consistent with previous reports,lgtandlspAmutations impaired growth in chemically defined media, but not in complex broth. MRSA exposure to the LspA inhibitor globomycin also increased β-lactam resistance. Mutation oflgtin anlspAbackground restored β-lactam resistance to wild type. ThelspAmutation had no effect on PBP2a expression, PG composition or autolytic activity indicating a potential role for WTA or LTA. ThelspAandlgtmutants exhibited marginally increased resistance to the D-alanine pathway inhibitor D-cycloserine. In addition, mutation oflgtand multicopylspAexpression, but not mutation oflspA, significantly increased susceptibility to the lipoteichoic acid synthase inhibitor Congo red revealing complex interplay between lipoprotein processing mutations and the expression/stability of cell surface glycopolymers. These findings indicate that accumulation of the LspA substrate, diacylglyceryl lipoprotein, increases MRSA resistance to β-lactam antibiotics through impacts on cell envelope components other than PG.
Nonsense-mediated decay is highly stable across individuals and tissues
Authors: Teran Nicole A. , Nachun Daniel , Eulalio Tiffany , Ferraro Nicole M. , Smail Craig , Rivas Manuel A. , Montgomery Stephen B.
Published: February 2021

Precise interpretation of the effects of protein-truncating variants (PTVs) is important for accurate determination of variant impact. Current methods for assessing the ability of PTVs to induce nonsense-mediated decay (NMD) focus primarily on the position of the variant in the transcript. We used RNA-sequencing of the Genotype Tissue Expression v8 cohort to compute the efficiency of NMD using allelic imbalance for 2,320 rare (genome aggregation database minor allele frequency <=1%) PTVs across 809 individuals in 49 tissues. We created an interpretable predictive model using penalized logistic regression in order to evaluate the comprehensive influence of variant annotation, tissue, and inter-individual variation on NMD. We found that variant position, allele frequency, including ultra-rare and singleton variants, and conservation were predictive of allelic imbalance. Furthermore, we found that NMD effects were highly concordant across tissues and individuals. Due to this high consistency, we demonstratein silicothat utilizing peripheral tissues or cell lines provides accurate prediction of NMD for PTVs.