bluuebunny/crossref_metadata_2025 huggingface dataset:
SAFB2 enables the processing of suboptimal stem-loop structures in clustered primary miRNA transcripts
Authors: Hutter Katharina , Lohmüller Michael , Jukic Almina , Eichin Felix , Avci Seymen , Labi Verena , Hoser Simon M. , Hüttenhofer Alexander , Villunger Andreas , Herzog Sebastian
Published: December 2019

MicroRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally silence most protein-coding genes in mammals. They are generated from primary transcripts containing single or multiple clustered stem-loop structures that are thought to be recognized and cleaved by the DGCR8/DROSHA Microprocessor complex as independent units. Contrasting this view, we here report an unexpected mode of processing of a bicistronic cluster of the miR-15 family, miR-15a-16-1. We find that the primary miR-15a stem-loop is a poor Microprocessor substrate and is consequently not processed on its own, but that the presence of the neighboring primary miR-16-1 stem-loop on the same transcript can compensate for this deficiency in cis. Using a CRISPR/Cas9 screen, we identify SAFB2 (scaffold attachment factor B2) as an essential co-factor in this miR-16-1-assisted pri-miR-15 cleavage, and describe SAFB2 as a novel accessory protein of DROSHA. Notably, SAFB2-mediated cluster assistance expands to other clustered pri-miRNAs including miR-15b, miR-92a and miR-181b, indicating a general mechanism. Together, our study reveals an unrecognized function of SAFB2 in miRNA processing and suggests a scenario in which SAFB2 enables the binding and processing of suboptimal DGCR8/DROSHA substrates in clustered primary miRNA transcripts.

Highlights

the primary miR-15a stem-loop structure per se is a poor Microprocessor substrate

cleavage of pri-miR-15a requires the processing of an additional miRNA stem-loop on the same RNA

sequential pri-miRNA processing or “cluster assistance” is mediated by SAFB proteins

SAFB2 associates with the Microprocessor
Zbtb24 binding protects promoter activity by antagonizing DNA methylation in mESCs
Authors: Wu Haoyu , Leon Granado David San , Vukic Maja , Vonk Kelly K.D. , Breukel Cor , Chouaref Jihed , Laros Jeroen F.J. , Daxinger Lucia
Published: December 2019

DNA methylation is a key epigenetic modification essential for normal development. How particular factors control DNA methylation patterns and activity of a given locus is incompletely understood. The zinc finger protein Zbtb24 has been implicated in transcriptional activation/repression and the DNA methylation maintenance pathway. Here, using whole genome bisulfite sequencing in mouse embryonic stem cells, we report that besides a general trend towards DNA hypomethylation, many genomic sites gain methylation in the absence of Zbtb24 and they include promoters of actively transcribed genes. DNA hypomethylation is not generally associated with gene expression changes, suggesting that additional epigenetic safeguards are in place that ensure silencing of the affected loci. Remarkably, we identify a set of genes that is particularly susceptible to Zbtb24 occupancy. At these sites, Zbtb24 binding is not only required for gene activity but also required for maintaining the unmethylated state of the promoter.
New, easy, quick and efficient DNA replication timing analysis by high-throughput approaches
Authors: Hadjadj Djihad , Denecker Thomas , Guérin Eva , Kim Su-Jung , Fauchereau Fabien , Baldacci Giuseppe , Maric Chrystelle , Cadoret Jean-Charles
Published: December 2019

DNA replication must be faithful and follow a well-defined spatio-temporal program closely linked to transcriptional activity, epigenomic marks, intra-nuclear structures, mutation rate and cell fate determination. Among the readouts of the DNA replication spatio-temporal program, replication timing (RT) analyses require complex, precise and time-consuming experimental procedures, and the study of large-size computer files. We improved the RT protocol to speed it up and increase its quality and reproducibility. Also, we partly automated the RT protocol and developed a user-friendly software: the START-R suite (Simple Tool for the Analysis of the Replication Timing based on R). START-R suite is an open source web application using an R script and an HTML interface to analyze DNA replication timing in a given cell line with microarray or deep-sequencing results. This novel approach can be used by every biologist without requiring specific knowledge in bioinformatics. It also reduces the time required for generating and analyzing simultaneously data from several samples. START-R suite detects constant timing regions (CTR) but also, and this is a novelty, it identifies temporal transition regions (TTR) and detects significant differences between two experimental conditions. The informatic global analysis requires less than 10 minutes.
Quantitative Analysis of Effects of a Single 60Co Gamma Ray Point Exposure on Time-Dependent Change in Locomotor Activity in Rats
Authors: Otani Keiko , Ohtaki Megu , Fujimoto Nariaki , Saimova Aisulu , Kairkhanova Ynkar , Uzbekov Darkhan , Chaizhunusova Nailya , Aukenov Nulran , Rakhypbekov Tolebay , Sato Hitoshi , Kawano Noriyuki , Hoshi Masaharu
Published: December 2019

Fatigue is one of the earliest nonspecific symptoms of radiation exposure in humans, but its etiology, mechanism, and dose dependency remain unexplained. Investigating initial behavioral changes caused by irradiation of animals might provide important information to aid understanding of early health effects of radiation exposure and clinical features of radiation injury. Although previous studies in rodents suggested that radiation exposure leads to reduced activity, detailed properties of the effects were unrevealed due to a lack of proper statistical analysis, which is needed to better elucidate details of changes in locomotor activity. Ten-week-old male Wistar rats were subjected to single point external whole-body irradiation with 60Co gamma rays at 0, 2.0, 3.5, and 5.0 Gy (4 rats per group). Infrared sensors were used to continuously record locomotor activity of each rat. Cumulative number of movements during the night was defined as “activity” for each day. A non-linear mixed effects model accounting for individual differences and daily fluctuation of activity was applied to analyze the rats’ longitudinal locomotor data. Despite a small number of animals per group, our statistical method successfully revealed characteristics of the changes in locomotor activity after radiation exposure, showing that 1) reduction in activity occurred immediately—and in a dose-dependent manner—after irradiation and 2) recovery to pre-irradiation levels required almost one week, with the same recovery rate in each dose group. In addition to improving our understanding of radiation effects on locomotor activity, this statistical framework should be useful to analyze other data with similar structure.
Investigating olfactory behaviors in adult zebrafish
Authors: Kermen Florence , Darnet Lea , Wiest Christoph , Palumbo Fabrizio , Bechert Jack , Uslu Ozge , Yaksi Emre
Published: December 2019

Odor-driven behaviors such as feeding, mating and predator avoidance are crucial for animal survival. While the zebrafish olfactory circuitry is well understood, a comprehensive description of odor-driven behaviors is needed to better relate olfactory computations to animal responses. Here, we used a medium-throughput setup to measure the swimming trajectories of 10 zebrafish in response to 17 ecologically relevant odors. By selecting appropriate locomotor metrics, we constructed ethograms systematically describing odor-induced changes in the swimming trajectory. We found that fish reacted to most odorants, using different behavioral programs and that combination of few relevant behavioral metrics enabled to capture most of the variance in these innate odor responses. We observed that monomolecular odors in similar chemical categories were weakly clustered based on the behavioral responses, likely because natural odors elicited stronger reactions than the monomolecular odors. Finally, we uncovered a previously undescribed intra and inter-individual variability of olfactory behaviors and suggest a small set of odors that elicit robust responses. In conclusion, our setup and results will be useful resources for future studies interested in characterizing olfactory responses in aquatic animals.
Unravelling ant-symbiont network topology across Europe
Authors: Parmentier Thomas , de Laender Frederik , Bonte Dries
Published: December 2019

Long-term associations between different species are key drivers in community composition in all ecosystems. Understanding the ecological and evolutionary drivers of these symbiotic associations is challenging because of the diversity of species and interaction types hosted in natural ecological networks. Here, we compiled the most complete database on natural ant-symbiont networks in Europe to identify the drivers of bipartite network topology. These ant-symbiont networks host an unrivalled diversity of symbiotic associations across the entire mutualism-antagonism continuum, of which the most diverse types of symbionts are (1) trophobionts: mutualistic aphids and scale insects (2) myrmecophiles: commensalistic and parasitic arthropods, and (3) social parasites: parasitic ant species. These diverse ant-symbiont networks provide a unique opportunity to tease apart ecological and evolutionary drivers. To do so, we dissected network topology and asked what determines host specificity and which host factors drive symbiont species richness and facilitate host switching for the different types of symbionts.

We found an unexpectedly high number of 701 obligate symbionts associated with European ants. Symbiont type explained host specificity and the average relatedness of the targeted host species. Social parasites were associated with few, but phylogenetically highly related hosts, whereas trophobionts and myrmecophiles interacted with a higher number of hosts across a wider taxonomic distribution. Colony size, host range and habitat type predicted total symbiont richness, where ants hosts with larger colony size or larger distribution range contained more symbiont species. However, we found that different sets of host factors affected diversity in the different types of symbionts. Ecological factors, such as colony size, host range and niche width predominantly drive myrmecophile species richness, whereas evolutionary factors, such as host phylogeny and biogeography, mainly determine richness of mutualistic trophobionts and social parasites. Lastly, we found that hosts with a common biogeographic history support a more similar community of symbionts. Phylogenetic related hosts also shared more trophobionts and social parasites, but not myrmecophiles. Taken together, these results suggest that ecological and evolutionary processes drive host specificity and symbiont richness in large-scale ant-symbiont networks, but these drivers may shift in importance depending on the type of symbiosis. Our findings highlight the potential of well-characterized bipartite networks composed of different types of symbioses to identify candidate processes driving community composition.
Feature matrix normalization, transformation and calculation of ß-diversity in metagenomics: Theoretical and applied perspectives on your decisions
Authors: Poulsen Casper Sahl , Aarestrup Frank Møller , Brinch Christian , Ekstrøm Claus Thorn
Published: December 2019

Microbial metagenomics utilising next generation sequencing is a powerful experimental approach enabling detailed and potentially complete descriptions of the microbial world around and within us. Selecting how to perform feature data normalization, transformation and calculate ß-diversity is a critical step in the analysis of metagenomic data, but also a step for which a multitude of methods are available. Researchers need to have a broad overview and understand the many methods that exist in the field and the consequences from applying them. In this perspectives article, some of the most widely used metagenomic feature data normalizations, transformations and ß-diversity metrics are discussed in the context of multivariate visualizations. We provide a framework that other researchers can utilize to evaluate how robust their test data are when applying different normalizations, transformations and ß-diversity metrics, and visually compare the results of the methods. We constructed an in silico test dataset to evaluate the setup and clarify how the theoretical discussion is transferable to this data. We urge other researchers to implement their own test data, normalization, transformation, ß-diversity metric and visualization methods, in the hope that it will advance better decision making both in study design and analysis strategy.
Adaptive Expansion of Taste Neuron Response Profiles by Congruent Aroma in Drosophila
Authors: Zhang Yiwen , Pu Yuhan , Zhang Yan , Cai Haini N. , Shen Ping
Published: December 2019

Pairing of food aroma with selected taste can lead to enhanced food flavor and eating euphoria, but how cross-modal sensory combinations are integrated to increase food reward value remains largely unclear. Here we report that combined stimulation by food aroma and taste drastically increased appetite in well-nourished Drosophila larvae, and the appetizing effect involves a previously uncharacterized smell-taste integration process at axon terminals of two Gr43a gustatory neurons. Molecular genetic analyses of the smell-taste integration reveal a G protein-mediated tuning mechanism in two central neuropeptide F (NPF) neurons. This mechanism converts selected odor stimuli to NPF-encoded appetizing signals that potentiate Gr43a neuronal response to otherwise non-stimulating glucose or oleic acid. Further, NPF-potentiated responses to glucose and oleic acid require a Gr43a-independent and Gr43a-dependent pathway, respectively. Our finding of adaptive expansion of taste neuron response profiles by congruent aroma reveals a previously uncharacterized layer of neural complexity in food flavor perception.
Constitutively enhanced genome integrity maintenance and direct stress mitigation characterize transcriptome of extreme stress-adaptedArabidopsis halleri
Authors: Lee Gwonjin , Ahmadi Hassan , Quintana Julia , Syllwasschy Lara , Janina Nadežda , Preite Veronica , Anderson Justin E. , Pietzenuk Björn , Krämer Ute
Published: December 2019

Heavy metal-rich toxic soils and ordinary soils are both natural habitats ofArabidopsis halleri. The molecular divergence underlying survival in sharply contrasting environments is unknown. Here we comparatively address metal physiology and transcriptomes ofA. hallerioriginating from the most highly heavy metal-contaminated soil in Europe, Ponte Nossa (Noss/IT), and from non-metalliferous (NM) soil. Noss exhibits enhanced hypertolerance and attenuated accumulation of cadmium (Cd), and transcriptomic Cd responsiveness is decreased, compared to plants of NM soil origin. Among the condition-independent transcriptome characteristics of Noss, the most highly overrepresented functional class of “meiotic cell cycle” comprises 21 transcripts with elevated abundance in vegetative tissues, in particularArgonaute 9(AGO9) and the synaptonemal complex transverse filament protein-encodingZYP1a/b. IncreasedAGO9transcript levels in Noss are accompanied by decreased long terminal repeat retrotransposon expression, and are shared by plants from milder metalliferous sites in Poland and Germany. Expression ofIron-regulated Transporter(IRT1) is very low and ofHeavy Metal ATPase 2(HMA2) strongly elevated in Noss, which can account for its specific Cd handling. In plants adapted to the most extreme abiotic stress, broadly enhanced functions comprise genes with likely roles in somatic genome integrity maintenance, accompanied by few alterations in stress-specific functional networks.
Antifungal activity of Ocotea odorifera (Vell.) Rowher, Ocotea puberula (Rich.) Nees and Cinnamodendron dinisii Schwanke essential oils
Authors: Mezzomo P. , Sausen T.L. , Paroul N. , Roman S.S. , Mielniczki A.A.P. , Cansian R.L.
Published: December 2019

Biocompounds are promising tools with the potential to control pathogenic microorganisms. The medicinal plant species Ocotea odorifera, Ocotea puberula and Cinnamodendron dinisii, distributed along Brazilian biomes, are sources of chemical compounds of biological interest. This study aimed to evaluate the antifungal activity of the essential oils of O. odorifera, O. puberula and C. dinisii essential oils upon the mycotoxin producers Alternaria alternata, Aspergillus flavus and Penicillium crustosum. The essential oils where characterized by gas chromatography coupled to mass spectrometer (CG-MS). The majority compounds identified were: safrol (39.23%) and camphor (31.54%) in O. odorifera, Beta-caryophyllene (25.01%) and spathulenol (17.74%) in O. puberula, and bicyclogermacrene (23.19%) and spathulenol (20.21%) in C. dinisii. The Minimal Inhibitory Concentration (MIC) of antifungal activity considered diameters higher than 10 mm after 72 h of incubation at 30 ºC. A. alternata presented higher resistance to O. odorifera and C. dinisii oils. The inhibitory effect of O. odorifera on A. flavus showed stabilization at oils concentrations between 50% and 80%, increasing at 90% and 100% (pure oil) treatments. We observed that the essential oils of O. odorifera and C. dinisii have potential in the control of the analyzed fungi species. The essential oil of O. odorifera presented a better activity in all the assays, which can be related to the presence of safrole and phenylpropenes, compounds with known antifungal activity.
Polymorphic inversions underlie the shared genetic susceptibility to prevalent common diseases
Authors: González Juan R , Ruiz-Arenas Carlos , Cáceres Alejandro , Morán Ignasi , López Marcos , Alonso Lorena , Tolosana Ignacio , Guindo-Martínez Marta , Mercader Josep M , Esko Tonu , Torrents David , González Josefa , Pérez-Jurado Luis A
Published: December 2019

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed the largest inversion association analysis to date, including 21 inversions and 25 obesity-related traits, on a total of 408,898 Europeans, and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2 and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes of obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.
Coinfinder: Detecting Significant Associations and Dissociations in Pangenomes
Authors: Whelan Fiona Jane , Rusilowicz Martin , McInerney James Oscar
Published: December 2019

2.

The accessory genes of prokaryote and eukaryote pangenomes accumulate by horizontal gene transfer, differential gene loss, and the effects of selection and drift. We have developed Coinfinder, a software program that assesses whether sets of homologous genes (gene families) in pangenomes associate or dissociate with each other (i.e. are “coincident”) more often than would be expected by chance. Coinfinder employs a user-supplied phylogenetic tree in order to assess the lineage-dependence (i.e. the phylogenetic distribution) of each accessory gene, allowing Coinfinder to focus on coincident gene pairs whose joint presence is not simply because they happened to appear in the same clade, but rather that they tend to appear together more often than expected across the phylogeny. Coinfinder is implemented in C++, Python3, and R and is freely available under the GPU license fromhttps://github.com/fwhelan/coinfinder.

3.

Impact statement

Coinfinder identifies genes that co-occur (associate) or avoid (dissociate) with each other across the accessory genomes of a pangenome of interest. Genes that associate or dissociate more often than expected by chance, suggests that those genes have a connection (attraction or repulsion) that is interesting to explore. Identification of these groups of genes will further the field’s understanding of the importance of accessory genes. Coinfinder is a freely available, open-source software which can identify gene patterns locally on a personal computer in a matter of hours.

4.

Data summary

Coinfinder is freely available athttps://github.com/fwhelan/coinfinder.

A list of the Identifiers of the genomes used within as well as all input/output files are available athttps://github.com/fwhelan/coinfinder-manuscript.

The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.
A simple device to immobilize protists for electrophysiology and microinjection
Authors: Kulkarni Anirudh , Escoubet Nicolas , Pontani Léa-Laetitia , Prevost Alexis Michel , Brette Romain
Published: December 2019

We present a simple device to mechanically immobilize motile cells such as ciliates and flagellates. It can be used in particular for intracellular electrophysiology and microinjection. A transparent filter with holes smaller than the specimen is stretched over an outlet. A flow is induced by either a peristaltic pump or a depressurized tank, mechanically entraining cells to the bottom, where they immobilize against the filter. The cells swim again freely as soon as the flow is stopped. We demonstrate the device by recording action potentials in Paramecium and injecting a fluorescent dye in the cytosol.
Microbial metabolically cohesive consortia and ecosystem functioning
Authors: Pascual-García Alberto , Bonhoeffer Sebastian , Bell Thomas
Published: December 2019

Recent theory and experiments have reported a reproducible tendency for the coexistence of microbial species under controlled environmental conditions. This observation has been explained in the context of competition for resources and metabolic complementarity given that, in microbial communities, many excreted by-products of metabolism may also be resources. Microbial communities therefore play a key role in promoting their own stability and in shaping the niches of the constituent taxa. We suggest that an intermediate level of organisation between the species and the community level may be pervasive, where tightly-knit metabolic interactions create discrete consortia that are stably maintained. We call these units Metabolically Cohesive Consortia (MeCoCos) and we discuss the environmental context in which we expect their formation, and the ecological and evolutionary consequences of their existence. We argue that the ability to identify MeCoCos would open new avenues to link the species-, community-, and ecosystem-level properties, with consequences for our understanding of microbial ecology and evolution, and an improved ability to predict ecosystem functioning in the wild.
Hardy-Weinberg Equilibrium in the Large Scale Genomic Sequencing Era
Authors: Abramovs Nikita , Brass Andrew , Tassabehji May
Published: December 2019

Hardy-Weinberg Equilibrium (HWE) is used to estimate the number of homozygous and heterozygous variant carriers based on its allele frequency in populations that are not evolving. Previously, deviation from HWE in large population databases were investigated to detect genotyping errors, which can result in extreme heterozygote excess (HetExc). However, HetExc might also be a sign of natural selection since recessive disease causing variants are expected to occur less frequently in a homozygous state in the general population, but might reach high allele frequency, especially if they are advantageous, in a heterozygote state. We developed a filtering strategy to detect these variants and applied it on genome data from 137,842 individuals. We found that the main limitations of this approach were quality of genotype calls and insufficient population sizes, whereas population structure and high level of inbreeding could reduce sensitivity, but not precision, in certain populations. Nevertheless, we identified 365 HetExc variants in 326 genes, most of which were specific to African/African American populations (~84.7%). Although the majority of them were not associated with known diseases, or were classified as “benign”, they were enriched in genes associated with autosomal recessive diseases. The resulting dataset also contained two known recessive disease causing variants with evidence of heterozygote advantage in the genes HBB and CFTR. Finally, we provide in silico evidence of a novel heterozygote advantageous variant in the CHD6 gene (involved in influenza virus replication). We anticipate that our approach will allow the detection of rare recessive disease causing variants in the future.
Volumetric Segmentation and Characterisation of the Paracingulate Sulcus on MRI Scans
Authors: Yang Junwei , Wang Duo , Rollins Colleen , Leming Matthew , Liò Pietro , Suckling John , Murray Graham , Garrison Jane , Cachia Arnaud
Published: December 2019

Many architectures of deep neural networks have been designed to solve specific biomedical problems, among which segmentation is a critical step to detect and locate the boundaries of the target object from an image. In this paper, we develop a deep learning based framework to automatically segment the paracingulate sulcus (PCS) from the MRI scan and estimate lengths for its segments. The study is the first work on segmentation and characterisation of the PCS, and the model achieves a Dice score of over 0.77 on segmentation, which demonstrates its potential for clinical use to assist human annotation. Moreover, the proposed architecture as a solution can be generalised to other problems where the object has similar patterns.
The PIWI protein Aubergine recruits eIF3 to activate translation in the germ plasm
Authors: Ramat Anne , Garcia-Silva Maria-Rosa , Jahan Camille , Naït-Saïdi Rima , Dufourt Jérémy , Garret Céline , Chartier Aymeric , Cremaschi Julie , Patel Vipul , Decourcelle Mathilde , Bastide Amandine , Juge François , Simonelig Martine
Published: December 2019

Piwi-interacting RNAs (piRNAs) and PIWI proteins are essential in germ cells to repress transposons and regulate mRNAs. InDrosophila, piRNAs bound to the PIWI protein Aubergine (Aub) are transferred maternally to the embryo and regulate maternal mRNA stability through two opposite roles. They target mRNAs by incomplete base-pairing, leading to both their destabilization in the soma, and stabilization in the germ plasm. Here, we report a function of Aub in translation. Aub is required for translational activation ofnanosmRNA, a key determinant of the germ plasm. Aub physically interacts with the poly(A) binding protein PABP and the translation initiation factor eIF3. Polysome gradient profiling identifies Aub role at the initiation step of translation. In the germ plasm, PABP and eIF3d assemble in foci that surround Aub-containing germ granules, and Aub acts with eIF3d to promotenanostranslation. These results reveal a new mode of mRNA regulation by Aub, highlighting PIWI protein versatility in mRNA regulation.
CDK4 as a phytochemical based anticancer drug target
Authors: Chando Rony Kumer , Hussain Nazmul , Rana Mashedul Islam , Sayed Shomoita , Alam Saruar , Fakir Tawkir Ahmed , Sharma Sudip , Tanu Arifur Rahman , Mobin Faraid , Apu Ehsanul Hoque , Hasan Kamrul , Sayed Abu , Ashraf Mohammad Arif
Published: December 2019

Success story of plant-based medicine had been overlooked during the advent of modern pharmaceutical industry. Despite the negligence of the multimillion-dollar drug industry, people entirely rely on medicinal plants in some part of the world. In this study, we have emphasized on going back to those traditional medicinal practices to figure out their underlying mechanism to move forward on phytochemical based drug development. We screened Medicinal Plant Database Bangladesh 1.0 (MPDB1.0) and on-going extension, MPDB2.0, of that database to find traditionally used medicinal plants and their active compounds. Here, Mangiferin, extracted from Mangifera indica, have been demonstrated to interact with cell cycle regulator Cyclin-dependent Kinase 4 (CDK4). CDK4 is differentially expressed during Glioblastoma multiforme (GBM), Brain Lower Grade Glioma (LGG), and Sarcoma (SARC). Expression of CDK4 is interlinked to the patients’ survival rate and its consistent expression throughout different stages have provided the advantage to use it as diagnostic tool and drug target. Altogether, this study demonstrated that simple mango tree extracted active compounds, mangiferin, can work as potential anticancer drug and leveraging the recent advancement of sequencing and gene expression data can accelerate the phytochemical based drug discovery process.
Variant effect predictions capture some aspects of deep mutational scanning experiments
Authors: Reeb Jonas , Wirth Theresa , Rost Burkhard
Published: December 2019

Deep mutational scanning (DMS) studies exploit the mutational landscape of sequence variation by systematically and comprehensively assaying the effect of single amino acid variants (SAVs) for particular proteins. Different experimental protocols proxy effect through a diversity of measures. We evaluated three early prediction methods trained on traditional variant effect data (PolyPhen-2, SIFT, SNAP2) along with a regression method optimized on DMS data (Envision). On a common subset of 32,981 SAVs, all methods capture some aspects of variant effects, albeit not the same. Early effect prediction methods correlated slightly more with measurements and better classified binary states (effect or neutral), while Envision predicted better the precise degree of effect. Most surprising was that a simple approach predicting residues conserved in families (found and aligned by PSI-BLAST) in many cases outperformed other methods. All methods predicted beneficial effects (gain-of-function) significantly worse than deleterious (loss-of-function). For the few proteins with several DMS measurements, experiments agreed more with each other than predictions with experiments. Our findings highlight challenges and opportunities of DMS for improving variant effect predictions.
Primary mammary organoid model of lactation and involution
Authors: Sumbal Jakub , Chiche Aurelie , Charifou Elsa , Koledova Zuzana , Li Han
Published: December 2019

Mammary gland development occurs mainly after birth and is composed of three successive stages: puberty, pregnancy and lactation, and involution. These developmental stages are associated with major tissue remodeling, including extensive changes in mammary epithelium as well as surrounding stroma. Three-dimensional (3D) mammary organoid culture has become an important tool in mammary gland biology and enabled invaluable discoveries on pubertal mammary branching morphogenesis and breast cancer. However, a suitable 3D organoid model recapitulating key aspects of lactation and involution has been missing. Here, we describe a robust and straightforward mouse mammary organoid system modeling lactation and involution-like process, which can be applied to study mechanisms of physiological mammary gland lactation and involution as well as pregnancy-associated breast cancer.
Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques
Authors: Xifra-Porxas Alba , Ghosh Arna , Mitsis Georgios D. , Boudrias Marie-Hélène
Published: December 2019

Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N=613, age 18-88 yrs) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 yrs) yielded worse performance when compared to using MRI features (MAE of 5.33 yrs), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 yrs). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.
Systematic detection of Mendelian and non-Mendelian variants associated with retinitis pigmentosa by genome-wide association study
Authors: Nishiguchi Koji M , Miya Fuyuki , Mori Yuka , Fujita Kosuke , Akiyama Masato , Kamatani Takashi , Koyanagi Yoshito , Kota Sato , Takigawa Toru , Ueno Shinji , Tsugita Misato , Kunikata Hiroshi , Cisarova Katarina , Nishino Jo , Murakami Akira , Abe Toshiaki , Momozawa Yukihide , Terasaki Hiroko , Wada Yuko , Sonoda Koh-Hei , Rivolta Carlo , Ishibashi Tatsuro , Tsunoda Tatsuhiko , Tsujikawa Motokazu , Ikeda Yasuhiro , Nakazawa Toru
Published: December 2019

To uncover genetic basis of autosomal recessive retinitis pigmentosa (ARRP), we applied 2-step genome-wide association study (GWAS) in 640 Japanese patients prescreened with targeted re-sequencing. Meta-GWAS identified three independent peaks atP< 5.0×10-8, all within the major ARRP geneEYS. Two were each tagged by a low frequency variant (allele frequency < 0.05); a known founder Mendelian mutation (c.4957dupA, p.S1653Kfs*2) and a presumably hypomorphic non-synonymous variant (c.2528G>A, p.G843E). c.2528G>A newly solved 7.0% of Japanese ARRP cases, improving genetic diagnosis by 26.8% and simultaneously serving as a new attractive target for genome editing gene therapy. The third peak was tagged by an intronic common variant, representing a novel disease-susceptibility signal. GWAS successfully unraveled genetic causes of a rare “monogenic” disorder for the first time, which provided unexpected insights into significant contribution of non-Mendelian genetic factors and identified a novel high frequency variant directly linked to development of local genome therapeutics.
Adaptation of plasticity to predicted climates in Australian rainbowfishes (Melanotaenia) across climatically defined bioregions
Authors: Sandoval-Castillo Jonathan , Gates Katie , Brauer Chris J. , Smith Steve , Bernatchez Louis , Beheregaray Luciano B.
Published: December 2019

Resilience to environmental stressors due to climate warming is influenced by local adaptations, including the capacity for plastic responses. The recent literature has focussed on genomic signatures of climatic adaptation, however little work has been done to address how plastic capacity may be influenced by biogeographic history and evolutionary processes. Here, we investigate phenotypic plasticity as a target of climatic selection, hypothesising that lineages that evolved under warmer climate will exhibit greater plastic adaptive resilience to thermal stress. This was tested using common garden experiments to compare gene expression regulation within and among a temperate, a subtropical and a desert ecotype of Australian rainbowfish. Individuals from each ecotype were subjected to contemporary and projected summer thermal conditions for 2070, and their global patterns of gene expression were characterized using liver transcriptomes. Critical thermal maximums were also determined for each ecotype to assess thermal tolerance. A comparative phylogenetic expression variance and evolution model framework was used to assess plastic and evolved changes in gene expression. Similar changes in both the direction and the magnitude of expressed genes were found within ecotypes. Although most expressed genes were identified in all ecotypes, 532 genes were identified as candidates subject to ecotype-specific directional selection. Twenty-three of those genes showed signal of adaptive (i.e. genetic-based) plastic response to future increases in temperature. Network analyses demonstrated centrality of these genes in thermal response pathways, along with several highly conserved hub genes thought to be integral for heat stress responses. The greatest adaptive resilience to warming was shown by the subtropical ecotype, followed by the desert and temperate ecotypes. Our findings indicate that vulnerability to climate change will be highly influenced by biogeographic factors, and we stress the need for integrative assessments of climatic adaptive traits for accurate estimations of population and ecosystem responses.
Mapping Human Pluripotent Stem Cell-Derived Erythroid Differentiation by Single-Cell Transcriptome Analysis
Authors: Xin Zijuan , Zhang Wei , Gong Shangjin , Zhu Junwei , Li Yanming , Zhang Zhaojun , Fang Xiangdong
Published: December 2019

There is an imbalance between the supply and demand of functional red blood cells (RBCs) in clinical applications. This imbalance can be addressed by regenerating RBCs using several in vitro methods. Induced pluripotent stem cells (iPSCs) can handle the low supply of cord blood and the ethical issues in embryonic stem cell research and provide a promising strategy to eliminate immune rejection. However, no complete single-cell level differentiation pathway exists for the iPSC-derived RBC differentiation system. In this study, we used iPSC line BC1 to establish a RBCs regeneration system. The 10× genomics single-cell transcriptome platform was used to map the cell lineage and differentiation trajectories on day 14 of the regeneration system. We observed that iPSCs differentiation was not synchronized during embryoid body (EB) culture. The cells (day 14) mainly consisted of mesodermal and various blood cells, similar to the yolk sac hematopoiesis. We identified six cell classifications and characterized the regulatory transcription factors (TFs) networks and cell-cell contacts underlying the system. iPSCs undergo two transformations during the differentiation trajectory, accompanied by the dynamic expression of cell adhesion molecules and estrogen-responsive genes. We identified different stages of erythroid cells such as burst-forming unit erythroid (BFU-E) and orthochromatic erythroblasts (ortho-E) and found that the regulation of TFs (e.g., TFDP1 and FOXO3) is erythroid-stage specific. Immune erythroid cells were identified in our system. This study provides systematic theoretical guidance for optimizing the iPSCs-derived RBCs differentiation system, and this system is a useful model for simulating in vivo hematopoietic development and differentiation.
Mini-batch optimization enables training of ODE models on large-scale datasets
Authors: Stapor Paul , Schmiester Leonard , Wierling Christoph , Lange Bodo M.H. , Weindl Daniel , Hasenauer Jan
Published: December 2019

Quantitative dynamical models are widely used to study cellular signal processing. A critical step in modeling is the estimation of unknown model parameters from experimental data. As model sizes and datasets are steadily growing, established parameter optimization approaches for mechanistic models become computationally extremely challenging. However, mini-batch optimization methods, as employed in deep learning, have better scaling properties. In this work, we adapt, apply, and benchmark mini-batch optimization for ordinary differential equation (ODE) models thereby establishing a direct link between dynamic modeling and machine learning. On our main application example, a large-scale model of cancer signaling, we benchmark mini-batch optimization against established methods, achieving better optimization results and reducing computation by more than an order of magnitude. We expect that our work will serve as a first step towards mini-batch optimization tailored to ODE models and enable modeling of even larger and more complex systems than what is currently possible.
Prioritized neural processing of social threats during perceptual decision-making
Authors: El Zein M. , Mennella R. , Sequestro M. , Meaux E. , Wyart V. , Grèzes J.
Published: December 2019

Emotional signals, notably those signaling threat, benefit from prioritized processing in the human brain. Yet, it remains unclear whether perceptual decisions about the emotional, threat-related aspects of stimuli involve specific or similar neural computations compared to decisions about their non-threatening/non-emotional components. We developed a novel behavioral paradigm in which participants performed two different detection tasks (emotion vs. color) on the same, two-dimensional visual stimuli. Electroencephalographic (EEG) activity in a cluster of central electrodes reflected the amount of perceptual evidence around 100ms following stimulus onset, when the decision concerned emotion, not color. Second, participants’ choice could be predicted earlier for emotion (240ms) than for color (380ms) by the mu (10Hz) rhythm, which reflects motor preparation. Taken together, these findings indicate that perceptual decisions about threat-signaling dimensions of facial displays are associated with prioritized neural coding in action-related brain regions, supporting the motivational value of socially relevant signals.
Astral microtubule crosslinking safeguards uniform nuclear distribution in the Drosophila syncytium
Authors: Deshpande Ojas , de-Carvalho Jorge , Vieira Diana V. , Telley Ivo A.
Published: December 2019

The early insect embryo develops as a multinucleated cell distributing the genome uniformly to the cell cortex. Mechanistic insight for nuclear positioning beyond cytoskeletal requirements is missing. Contemporary hypotheses propose actomyosin driven cytoplasmic movement transporting nuclei, or repulsion of neighbor nuclei driven by microtubule motors. Here, we show that microtubule crosslinking by Feo and Klp3A is essential for nuclear distribution and internuclear distance maintenance in Drosophila. Germline knockdown causes irregular, less dense nuclear delivery to the cell cortex and smaller distribution in ex vivo embryo explants. A minimal internuclear distance is maintained in explants from control embryos but not from Feo inhibited embryos, following micromanipulation assisted repositioning. A dimerization deficient Feo abolishes nuclear separation in embryo explants while the full-length protein rescues the genetic knockdown. We conclude that Feo and Klp3A crosslinking of antiparallel microtubule overlap generates a length-regulated mechanical link between neighboring microtubule asters. Enabled by a novel experimental approach, our study illuminates an essential process of embryonic multicellularity.
A machine learning based approach to the segmentation of micro CT data in archaeological and evolutionary sciences
Authors: O’Mahoney Thomas , Mcknight Lidija , Lowe Tristan , Mednikova Maria , Dunn Jacob
Published: December 2019

Segmentation of high-resolution tomographic data is often an extremely time-consuming task and until recently, has usually relied upon researchers manually selecting materials of interest slice by slice. With the exponential rise in datasets being acquired, this is clearly not a sustainable workflow. In this paper, we apply the Trainable Weka Segmentation (a freely available plugin for the multiplatform program ImageJ) to typical datasets found in archaeological and evolutionary sciences. We demonstrate that Trainable Weka Segmentation can provide a fast and robust method for segmentation and is as effective as other leading-edge machine learning segmentation techniques.
Intramembrane cleavage of TREM2 is determined by its intrinsic structural dynamics
Authors: Steiner Andrea , Schlepckow Kai , Brunner Bettina , Steiner Harald , Haass Christian , Hagn Franz
Published: December 2019

Sequence variants of the microglial expressed TREM2 (triggering receptor expressed on myeloid cells 2) are a major risk factor for late onset Alzheimer’s disease. TREM2 requires a stable interaction with DAP12 in the membrane to initiate signaling, which is terminated by TREM2 ectodomain shedding and subsequent intramembrane cleavage by γ-secretase. To understand the structural basis for the specificity of the intramembrane cleavage event, we determined the solution structure of the TREM2 transmembrane helix (TMH). Due to the presence of a charged amino acid in the membrane region the TREM2-TMH adopts a kinked structure with increased flexibility. Charge removal leads to TMH stabilization and reduced dynamics, similar to its structure in complex with DAP12. Strikingly, these dynamical features perfectly correlate with the site of the initial γ-secretase cleavage event. These data suggest an unprecedented cleavage mechanism by γ-secretase where flexible TMH regions are identified to initiate substrate cleavage.
Infection risk and extensive parental care govern the molecular evolution of Toll-like receptors in birds
Authors: Zhang Zhechun , Liang Dan , Chen Guoling , Zou Fasheng , Lei Fumin , Dong Lu , Griesser Michael , Liu Yang
Published: December 2019

The arms race between pathogens and the immune system of their hosts is a critical evolutionary force that affects the ecology and life history of organisms. An increased infection risk selects for adaptations in immune genes that encode receptors involved in pathogen recognition and the initiation of innate immune responses, including Toll-like receptor (TLR) genes. Although recent studies assessed the evolution of major histocompatibility complex (MHC) genes, the ecological and evolutionary processes that drive the evolution of immune genes across major phylogenetic lineages remain unstudied. Moreover, trade-offs between immune responses and other energy-demanding vital functions may limit the resource allocation into costly immune functions, and therefore affect the evolution of immune genes. Here we assess the evolutionary patterns of six TLR genes across 121 bird species, covering 95% of extant orders that represent diverse ecologies and life histories. Selection analyses revealed that all six TLR genes show strong signs of purifying selection, while few sites underwent episodic positive selection. Comparative phylogenetic analyses showed that the intensity of positive selection of TLR genes is associated with long-distance migration, extensive parental care (i.e., altricality and prolonged parent-offspring association), and a large body size (a proxy of increased longevity). Together, these results suggest that the evolution of immune genes is characterized by episodic positive selection, and is shaped by an increased inflection risk and extensive parental care that buffers the costs of immune functions.