bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved detection of evolutionary selection highlights potential bias from different sequencing strategies in complex genomic-regions
Authors: Hayeck Tristan J. , Li Yang , Mosbruger Timothy L. , Bradfield Jonathan P , Gleason Adam G. , Damianos George , Shaw Grace Tzun-Wen , Duke Jamie L. , Conlin Laura K. , Turner Tychele N. , Fernández-Viña Marcelo A. , Sarmady Mahdi , Monos Dimitri S.
Published: October 2021

Balancing selection occurs when multiple alleles are kept at elevated frequencies in equilibrium due to opposing evolutionary pressures. A new statistical method was developed to test for selection using efficient Bayesian techniques. Selection signals in three different data sets, generated with variable sequencing technologies, were compared: clinical trios, HLA NGS typed samples, and whole-genome long-read samples. Genome-wide, selection was observed across multiple gene families whose biological functions favor diversification, revealing established targets as well as 45 novel genes under selection. Using high-resolution HLA typing and long-read sequencing data, for the characterization of the MHC, revealed strong selection in expected peptide-binding domains as well as previously understudied intronic and intergenic regions of the MHC. Surprisingly, SIRPA, demonstrated dramatic selection signal, second only to the MHC in most settings. In conclusion, employing novel statistical approaches and improved sequencing technologies is critical to properly analyze complex genomic regions.
Enhanced nociceptive behavior and expansion of associated primary afferents in a rabbit model of cerebral palsy
Authors: Reedich E. J. , Genry L. T. , Singer M. A. , Cavarsan C. F. , Mena Avila E. , Boudreau D. M. , Brennan M. C. , Garrett A. M. , Dowaliby L. , Detloff M. R. , Quinlan K. A.
Published: October 2021

Spastic cerebral palsy (CP) is a movement disorder marked by hypertonia and hyperreflexia, and the most prevalent comorbidity is pain. Since spinal nociceptive afferents contribute to both the sensation of painful stimuli as well as reflex circuits involved in movement, we investigated the relationship between prenatal hypoxia-ischemia (HI) injury which can cause CP, and possible changes in spinal nociceptive circuitry. To do this, we examined nociceptive afferents and mechanical and thermal sensitivity of New Zealand White rabbit kits after prenatal HI or a sham surgical procedure. As described previously, a range of motor deficits similar to spastic CP was observed in kits born naturally after HI (40 minutes at ∼70-80% gestation). We found that HI caused an expansion of peptidergic afferents (marked by expression of calcitonin gene-related peptide; CGRP) in both the superficial and deep dorsal horn at postnatal day (P)5. Non-peptidergic nociceptive afferent arborization (labeled by isolectin B4; IB4) was unaltered in HI kits but overlap of the two populations (peptidergic and non-peptidergic nociceptors) was increased by HI. Density of glial fibrillary acidic protein (GFAP) was unchanged within spinal white matter regions important in nociceptive transmission at P5. We found that mechanical and thermal nociception was enhanced in HI kits even in the absence of motor deficits. These findings suggest that prenatal HI injury impacts spinal sensory pathways in addition to the more well-established disruptions to descending motor circuits. In conclusion, changes to spinal nociceptive circuitry could disrupt spinalreflexes and contribute to pain experienced by individuals with CP.

Significance Statement

Perinatal injuries that cause cerebral palsy (CP) typically involve global insults to the central nervous system and are capable of modulating development of both motor and sensory systems. Most individuals with CP experience pain, yet whether nociception is enhanced in this disorder is unexplored. Here, we demonstrate altered topographic distribution of nociceptive afferents in the spinal cord dorsal horn of neonatal rabbits that experienced hypoxic-ischemic (HI) injury in utero; these anatomical changes were associated with nocifensive behavior indicative of pain-like behaviors. Our findings suggest that CP-causative injuries alter spinal sensory pathways (not only descending motor circuits), contributing to increased pain in CP.
Nanocrown electrodes for reliable and robust intracellular recording of cardiomyocytes and cardiotoxicity screening
Authors: Jahed Zeinab , Yang Yang , Tsai Ching-Ting , Foster Ethan P. , McGuire Allister F. , Yang Huaxiao , Liu Aofei , Forro Csaba , Yan Zen , Jiang Xin , Zhao Ming-Tao , Zhang Wei , Li Xiao , Li Thomas , Pawlosky Annalisa , Wu Joseph C. , Cui Bianxiao
Published: October 2021

Drug-induced cardiotoxicity arises primarily when a compound alters the electrophysiological properties of cardiomyocytes. Features of intracellular action potentials (iAPs) are powerful biomarkers that predict proarrhythmic risks. However, the conventional patch clamp techniques for measuring iAPs are either laborious and low throughput or not suitable for measuring electrically connected cardiomyocytes. In the last decade, a number of vertical nanoelectrodes have been demonstrated to achieve parallel and minimally-invasive iAP recordings. Nanoelectrodes show great promise, but the large variability in success rate, signal strength, and the low throughput of device fabrication have hindered them from being broadly adopted for proarrhythmia drug assessment. In this work, we developed vertically-aligned and semi-hollow nanocrown electrodes that are mechanically robust and made through a scalable fabrication process. Nanocrown electrodes achieve >99% success rates in obtaining intracellular access through electroporation, allowing reliable and simultaneous iAP recordings from up to 57 human pluripotent stem-cell-derived cardiomyocytes (hPSC-CMs). The accuracy of nanocrown electrode recordings is validated by simultaneous patch clamp recording from the same cell. Nanocrown electrodes enable prolonged iAP recording for continual monitoring of the same cells upon the sequential addition of four to five incremental drug doses. In this way, the dose-response data is self-referencing, which avoids the cell-to-cell variations inherent to hPSC-CMs. We are hopeful that this technology development is a step towards establishing an iAP screening assay for preclinical evaluation of drug-induced arrhythmogenicity.
Redundant functions of the SLC5A transporters Rumpel Kumpel and Bumpel in ensheathing glial cells
Authors: Yildirim Kerem , Winkler Bente , Pogodalla Nicole , Mackensen Steffi , Baldenius Marie , Garcia Luis , Naffin Elke , Rodrigues Silke , Klämbt Christian
Published: October 2021

Neuronal processing is energy demanding, and relies on sugar metabolism as an energy source. To provide a constant metabolite supply neurons and glial cells express many glucose and lactate transporters of the solute carrier (SLC) 5A family. Here we dissect the partially redundant functions of three highly related glia specific Drosophila genes encoding SLC5A proteins, Rumpel, Bumpel and Kumpel. While knockdown of rumpel causes several behavioral phenotypes, they are less prominent in rumpel mutants. bumpel and kumpel mutants are viable and fertile, lacking discernible phenotypes. However, in bumpel kumpel double mutants and to an even greater extent in rumpel bumpel kumpel triple mutants oogenesis is disrupted at the onset of the vitollegenic phase. This indicates at least partially redundant functions between these genes. Rescue experiments exploring this effect indicate that oogenesis can be affected by CNS glial cells. Moreover, expression of heterologous mammalian SLC5A transporter proteins, with known transport properties, suggest that Bumpel and/or Kumpel transport glucose or lactate. Overall, our results imply a redundancy in SLC5A nutrient sensing functions in Drosophila glial cells, affecting ovarian development and behavior.
Computational Fingerprints: Modeling Interactions Between Brain Regions as Points in a Function Space
Authors: Poskanzer Craig , Anzellotti Stefano
Published: October 2021

In this paper we propose a novel technique to investigate the nonlinear interactions between brain regions that captures both the strength and the type of the functional relationship. Inspired by the field of functional analysis, we propose that the relationship between activity in two different brain areas can be viewed as a point in function space, identified by coordinates along an infinite set of basis functions. Using Hermite Polynomials as basis functions, we estimate from fMRI data a truncated set of coordinates that serve as a “computational fingerprint,” characterizing the interaction between two brain areas. We provide a proof of the convergence of the estimates in the limit, and we validate the method with simulations in which the ground truth is known, additionally showing that computational fingerprints detect statistical dependence also when correlations (“functional connectivity”) is near zero. We then use computational fingerprints to examine the neural interactions with a seed region of choice: the Fusiform Face Area (FFA). Using k-means clustering across each voxel’s computational fingerprint, we illustrate that the addition of the nonlinear basis functions allows for the discrimination of inter-regional interactions that are otherwise grouped together when only linear dependence is used. Finally, we show that regions in V5 and medial occipital and temporal lobes exhibit significant nonlinear interactions with the FFA.
Cell-ACDC: a user-friendly toolset embedding state-of-the-art neural networks for segmentation, tracking and cell cycle annotations of live-cell imaging data
Authors: Padovani Francesco , Mairhörmann Benedikt , Falter-Braun Pascal , Lengefeld Jette , Schmoller Kurt M.
Published: October 2021

Live-cell imaging is a powerful tool to study dynamic cellular processes on the level of single cells with quantitative detail. Microfluidics enables parallel high-throughput imaging, creating a downstream bottleneck at the stage of data analysis. Recent progress on deep learning image analysis dramatically improved cell segmentation and tracking. Nevertheless, manual data validation and correction is typically still required and broadly used tools spanning the complete range of live-cell imaging analysis, from cell segmentation to pedigree analysis and signal quantification, are still needed. Here, we present Cell-ACDC, a user-friendly graphical user-interface (GUI)-based framework written in Python, for segmentation, tracking and cell cycle annotation. We included two state-of-the-art and high-accuracy deep learning models for single-cell segmentation of yeast and mammalian cells implemented in the most used deep learning frameworks TensorFlow and PyTorch. Additionally, we developed and implemented a cell tracking method and embedded it into an intuitive, semi-automated workflow for label-free cell cycle annotation of single cells. The open-source and modularized nature of Cell-ACDC will enable simple and fast integration of new deep learning-based and traditional methods for cell segmentation or downstream image analysis.

Source code

https://github.com/SchmollerLab/Cell_ACDC
Numb reduces Tau levels and prevents neurodegeneration in mouse models of tauopathy in an isoform-specific manner
Authors: Lacomme Marine , Hales Sarah C. , Stevanovic Katarina , Jolicoeur Christine , Bois Therence , Cai Jenny , Desrosiers Melissa , Dalkara Deniz , Cayouette Michel
Published: October 2021

Accumulation of the microtubule-associated protein Tau is linked to neuronal cell death in tauopathies, but how exactly intraneuronal Tau levels are regulated in health and disease remains unclear. Here we identify the trafficking adaptor protein Numb as an essential regulator of Tau homeostasis. Conditional inactivation of Numb in retinal ganglion cells (RGCs) increases monomeric and oligomeric Tau levels, leading to axonal blebbing followed by neuronal cell loss in aged mice. Moreover, in a mouse model of tauopathy, inactivation of Numb in RGCs and spinal motoneurons accelerates neurodegeneration, and leads to precocious hindlimb paralysis. Conversely, overexpression of the long isoform of Numb (Numb-72), but not other isoforms, decreases intracellular Tau levels by promoting the extracellular release of monomeric Tau, and AAV-mediated delivery of Numb-72 in RGCs in vivo prevents neurodegeneration in two different mouse models of tauopathy. Taken together, these results uncover Numb as a modulator of intracellular Tau levels and identify Numb-72 as a novel therapeutic factor for tauopathies.
Enhanced Production of Mesencephalic Dopaminergic Neurons from Lineage-Restricted Human Undifferentiated Stem Cells
Authors: Maimaitili Muyesier , Chen Muwan , Febbraro Fabia , Mermet-Joret Noëmie , Lauritsen Johanne , Ucuncu Ekin , Klæstrup Ida Hyllen , Qvist Per , Nabavi Sadegh , Romero-Ramos Marina , Denham Mark
Published: October 2021

The differentiation of human pluripotent stem cells (hPSCs) into mesencephalic dopaminergic (mesDA) neurons requires a precise combination of extrinsic factors that recapitulates the in vivo environment and timing. Current methods are capable of generating authentic mesDA neurons after long-term culture in vitro; however, when mesDA progenitors are transplanted in vivo, the resulting mesDA neurons are only minor components of the graft. This low yield hampers the broad use of these cells in the clinic. In this study, we genetically modified pluripotent stem cells to generate a novel type of stem cells called lineage-restricted undifferentiated stem cells (LR-USCs), which robustly generate mesDA neurons. LR-USCs are prevented from differentiating into a broad range of nondopaminergic cell types by knocking out genes that are critical for the specification of cells of alternate lineages. Specifically, we target transcription factors involved in the production of spinal cord and posterior hindbrain cell types. When LR-USCs are differentiated under caudalizing condition, which normally give rise to hindbrain cell types, a large proportion adopt a midbrain identity and develop into authentic mesDA neurons. We show that the mesDA neurons are electrophysiologically active, and due to their higher purity, are capable of restoring motor behavior eight weeks after transplantation into 6-hydroxydopamine (6-OHDA)-lesioned rats. This novel strategy improves the reliability and scalability of mesDA neuron generation for clinical use.
Survival Genie, a web platform for survival analysis across pediatric and adult cancers
Authors: Dwivedi Bhakti , Mumme Hope , Satpathy Sarthak , Bhasin Swati S. , Bhasin Manoj
Published: October 2021

The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number of packages and tools have been developed to correlate gene expression/mutations to the clinical outcome but lack the ability to perform such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-Seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-Seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile.

The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/.
Tracking chromatin state changes using μMap photo-proximity labeling
Authors: Seath Ciaran P. , Burton Antony J. , MacMillan David W. C. , Muir Tom W.
Published: October 2021

Interactions between biomolecules, particularly proteins, underlie all cellular processes, and ultimately control cell fate. Perturbation of native interactions through mutation, changes in expression levels, or external stimuli leads to altered cellular physiology and can result in either disease or therapeutic effects.1,2 Mapping these interactions and determining how they respond to stimulus is the genesis of many drug development efforts, leading to new therapeutic targets and improvements in human health.1 However, in the complex environment of the nucleus it is challenging to determine protein-protein interactions due to low abundance, transient or multi-valent binding, and a lack of technologies that are able to interrogate these interactions without disrupting the protein binding surface under study.3 Chromatin remodelers, modifying enzymes, interactors, and transcription factors can all be redirected by subtle changes to the microenvironment, causing global changes in protein expression levels and subsequent physiology. Here, we describe the Chroma-μMap method for the traceless incorporation of Ir-photosensitizers into the nuclear microenvironment using engineered split inteins. These Ir-catalysts can activate diazirine warheads to form reactive carbenes within a ~10 nm radius, cross-linking with proteins within the immediate microenvironment for analysis via quantitative chemoproteomics.4 We demonstrate this concept on nine different nuclear proteins with varied function and in each case, elucidating their microenvironments. Additionally, we show that this short-range proximity labeling method can reveal the critical changes in interactomes in the presence of cancer-associated mutations, as well as treatment with small-molecule inhibitors. Chroma-μMap improves our fundamental understanding of nuclear protein-protein interactions, as well as the effects that small molecule therapeutics have on the local chromatin environment, and in doing so is expected to have a significant impact on the field of epigenetic drug discovery in both academia and industry.
SSAM-lite: a light-weight web app for rapid analysis of spatially resolved transcriptomics data
Authors: Tiesmeyer Sebastian , Sahay Shashwat , Müller-Bötticher Niklas , Eils Roland , Mackowiak Sebastian D. , Ishaque Naveed
Published: October 2021

1

The combination of a cell’s transcriptional profile and location defines its function in a spatial context. Spatially resolved transcriptomics (SRT) has emerged as the assay of choice for characterizing cells in situ. SRT methods can resolve gene expression up to single-molecule resolution. A particular computational problem with single-molecule SRT methods is the correct aggregation of mRNA molecules into cells. Traditionally, aggregating mRNA molecules into cell-based features begins with the identification of cells via segmentation of the nucleus or the cell membrane. However, recently a number of cell-segmentation-free approaches have emerged. While these methods have been demonstrated to be more performant than segmentation-based approaches, they are still not easily accessible since they require specialized knowledge of programming languages and access to large computational resources. Here we present SSAM-lite, a tool that provides an easy-to-use graphical interface to perform rapid and segmentation-free cell-typing of SRT data in a web browser. SSAM-lite runs locally and does not require computational experts or specialized hardware. Analysis of a tissue slice of the mouse somatosensory cortex took less than a minute on a laptop with modest hardware. Parameters can interactively be optimized on small portions of the data before the entire tissue image is analyzed. A server version of SSAM-lite can be run completely offline using local infrastructure. Overall, SSAM-lite is portable, lightweight, and easy to use, thus enabling a broad audience to investigate and analyze single-molecule SRT data.

Availability and Implementation

SSAM-lite is an open-source browser-based web application with source code freely available on Github via https://github.com/HiDiHlabs/ssam-lite. Stable releases can be accessed via https://ssam-lite.bihealth.org and https://ssam-lite.netlify.app, and developmental releases can be accessed via https://dev--ssam-lite.netlify.app. The source code for a locally deployable server version, SSAM-lite-server, is available on GitHub via https://github.com/HiDiHlabs/ssam-lite-server. Both versions require a modern browser with JavaScript and WebGL support. Detailed user guides and documentation can be found at https://ssam-lite.readthedocs.io.
Experimental evidence for the impact of soil viruses on carbon cycling during surface plant litter decomposition
Authors: Albright Michaeline B.N. , Gallegos-Graves La Verne , Feeser Kelli L. , Montoya Kyana , Emerson Joanne B. , Shakya Migun , Dunbar John
Published: October 2021

To date, the potential impact of viral communities on biogeochemical cycles in soil has largely been inferred from indirect evidence, such as virus-driven changes in microbial abundances, viral auxiliary metabolic genes, and correlations with soil physiochemical properties. To more directly test the impact of soil viruses on carbon cycling during plant litter decomposition, we added concentrated viral community suspensions to complex litter decomposer communities in 40-day microcosm experiments. Microbial communities from two New Mexico alpine soils, Pajarito (PJ) and Santa Fe (SF), were inoculated onto grass litter on sand, and three treatments were applied in triplicate to each set of microcosms: addition of buffer (no added virus), addition of live virus (+virus), or killed virus (+killed-virus) fractions extracted from the same soil. Significant differences in respiration were observed between the +virus and +killed-virus treatments in the PJ, but not the SF microcosms. Bacterial and fungal community composition differed significantly by treatment in both PJ and SF microcosms. Combining data across both soils, viral addition altered links between bacterial and fungal diversity, dissolved organic carbon and total nitrogen. Overall, we demonstrate that increasing viral pressure in complex microbial communities can impact terrestrial biogeochemical cycling but is context-dependent.
Constructing benchmark test sets for biological sequence analysis using independent set algorithms
Authors: Petti Samantha N. , Eddy Sean R.
Published: October 2021

Statistical inference and machine learning methods are benchmarked on test data independent of the data used to train the method. Biological sequence families are highly non-independent because they are related by evolution, so the strategy for splitting data into separate training and test sets is a nontrivial choice in benchmarking sequence analysis methods. A random split is insufficient because it will yield test sequences that are closely related or even identical to training sequences. Adapting ideas from independent set graph algorithms, we describe two new methods for splitting sequence data into dissimilar training and test sets. These algorithms input a sequence family and produce a split in which each test sequence is less than p% identical to any individual training sequence. These algorithms successfully split more families than a previous approach, enabling construction of more diverse benchmark datasets.
Decoding Estimates of Curvilinear Self-Motion from Neural Signals in a Model of Primate MSTd
Authors: Layton Oliver W. , Powell Nathaniel , Steinmetz Scott T , Fajen Brett R
Published: October 2021

Self-motion produces characteristic patterns of optic flow on the eye of the mobile observer. Movement along linear, straight paths without eye movements yields motion that radiates from the direction of travel (heading). The observer experiences more complex motion patterns while moving along more general curvilinear (e.g. circular) paths, the appearance of which depends on the radius of the curved path (path curvature) and the direction of gaze. Neurons in brain area MSTd of primate visual cortex exhibit tuning to radial motion patterns and have been linked with linear heading perception. MSTd also contains neurons that exhibit tuning to spirals, but their function is not well understood. We investigated in a computational model whether MSTd, through its diverse pattern tuning, could support estimation of a broader range of self-motion parameters from optic flow than has been previously demonstrated. We used deep learning to decode these parameters from signals produced by neurons tuned to radial expansion, spiral, ground flow, and other patterns in a mechanistic neural model of MSTd. Specifically, we found that we could accurately decode the clockwise/counterclockwise sign of curvilinear path and the gaze direction relative to the path tangent from spiral cells; heading from radial cells; and the curvature (radius) of the curvilinear path from activation produced by both radial and spiral populations. We demonstrate accurate decoding of these linear and curvilinear self-motion parameters in both synthetic and naturalistic videos of simulated self-motion. Estimates remained stable over time, while also rapidly adapting to dynamic changes in the observer’s curvilinear self-motion. Our findings suggest that specific populations of neurons in MSTd could effectively signal important aspects of the observer’s linear and curvilinear self-motion.

Author Summary

How do we perceive our self-motion as we move through the world? Substantial evidence indicates that brain area MSTd contains neurons that signal the direction of travel during movement along straight paths. We wondered whether MSTd neurons could also estimate more general self-motion along curved paths. We tested this idea by using deep learning to decode signals produced by a neural model of MSTd. The system accurately decoded parameters that specify the observer’s self-motion along straight and curved paths in videos of synthetic and naturalistic scenes rendered in the Unreal game engine. Our findings suggest that MSTd could jointly signal self-motion along straight and curved paths.
Assessing sequence-based protein-protein interaction predictors for use in therapeutic peptide engineering
Authors: Charih François , Biggar Kyle K. , Green James R.
Published: October 2021

Engineering peptides to achieve a desired therapeutic effect through the inhibition of a specific target activity or protein interaction is a non-trivial task. Few of the existing in silico peptide design algorithms generate target-specific peptides. Instead, many methods produce peptides that achieve a desired effect through an unknown mechanism. In contrast with resource-intensive high-throughput experiments, in silico screening is a cost-effective alternative that can prune the space of candidates when engineering target-specific peptides. Using a set of FDA-approved peptides we curated specifically for this task, we assess the applicability of several sequence-based protein-protein interaction predictors as a screening tool within the context of peptide therapeutic engineering. We show that similarity-based protein-protein interaction predictors are more suitable for this purpose than the state-of-the-art deep learning methods publicly available at the time of writing. We also show that this approach is mostly useful when designing new peptides against targets for which naturally-occurring interactors are already known, and that deploying it for de novo peptide engineering tasks may require gathering additional target-specific training data. Taken together, this work offers evidence that supports the use of similarity-based protein-protein interaction predictors for peptide therapeutic engineering, especially peptide analogs.
Investigating the genetic architecture of eye colour in a Canadian cohort
Authors: Lona-Durazo Frida , Thakur Rohit , Pairo-Castineira Erola , Funderburk Karen , Zhang Tongwu , Kovacs Michael A. , Choi Jiyeon , Jackson Ian J. , Brown Kevin M. , Parra Esteban J.
Published: October 2021

The main factors that determine eye colour are the amount of melanin concentrated in iris melanocytes, as well as the shape and distribution of melanosomes. Eye colour is highly variable in populations with European ancestry, in which eye colour categories cover a continuum of low to high quantities of melanin accumulated in the iris. A few polymorphisms in the HERC2/OCA2 locus in chromosome 15 have the largest effect on eye colour in these populations, although there is evidence of other variants in the locus and across the genome also influencing eye colour. To improve our understanding of the genetic loci determining eye colour, we performed a meta-analysis of genome-wide association studies in a Canadian cohort of European ancestry (N= 5,641) and investigated putative causal variants. Our fine-mapping results indicate that there are several candidate causal signals in the HERC2/OCA2 region, whereas other significant loci in the genome likely harbour a single causal signal (TYR, TYRP1, IRF4, SLC24A4). Furthermore, a short subset of the associated eye colour regions was colocalized with the gene expression or methylation profiles of cultured melanocytes (HERC2, OCA2), and transcriptome-wide association studies highlighted the expression of two genes associated with eye colour: SLC24A4 and OCA2. Finally, genetic correlations of eye and hair colour from the same cohort suggest high pleiotropy at the genome level, but locus-level evidence hints at several differences in the genetic architecture of both traits. Overall, we provide a better picture of how polymorphisms modulate eye colour variation, particularly in the HERC2/OCA2 locus, which may be a consequence of specific molecular processes in the iris melanocytes.

Author Summary

Eye colour differences among humans are the result of different amounts of melanin produced, as well as due to differences in the shape and distribution of the organelles in charge of producing melanin. Eye colour is a highly heritable trait, where several genes across the genome are involved in the process, but we currently do not fully understand which are the causal variants and how they modulate eye colour variation. By performing genome-wide association studies of eye colour across Canadian individuals of European ancestry, we identify several candidate causal signals in and near the gene OCA2, and one candidate signal in other genes, such as TYR, TYRP1, IRF4 and SLC24A4. Furthermore, we provide insights about how significant loci may modulate eye colour variation by testing for shared signals with polymorphisms associated with the expression of genes and DNA methylation. Overall, we provide a better picture of the genetic architecture of eye colour and the molecular mechanisms contributing to its variation.
The kinesin KIF4 mediates HBV/HDV entry through regulation of surface NTCP localization and can be targeted by RXR agonistsin vitro
Authors: Gad Sameh A. , Sugiyama Masaya , Tsuge Masataka , Wakae Kosho , Fukano Kento , Oshima Mizuki , Sureau Camille , Watanabe Noriyuki , Kato Takanobu , Murayama Asako , Li Yingfang , Shoji Ikuo , Shimotohno Kunitada , Chayama Kazuaki , Muramatsu Masamichi , Wakita Takaji , Nozaki Tomoyoshi , Aly Hussein H.
Published: October 2021

Intracellular transport via microtubule-based dynein and kinesin family motors plays a key role in viral reproduction and transmission. We show here that Kinesin Family Member 4 (KIF4) plays an important role in HBV/HDV infection. We intended to explore host factors impacting the HBV life cycle that can be therapeutically addressed using siRNA library transfection and HBV/NLuc (HBV/NL) reporter virus infection in HepG2-hNTCP C4 cells. KIF4 silencing resulted in a 3-fold reduction in luciferase activity following HBV/NL infection and suppressed both wild-type HBV and HDV infection. Transient KIF4 depletion reduced surface and raised intracellular NTCP (HBV/HDV entry receptor) levels, according to both cellular fractionation and immunofluorescence analysis (IF). Overexpression of wild-type KIF4 but not ATPase-null KIF4 regains the surface localization of NTCP in these cells. Furthermore, immunofluorescence (IF) revealed KIF4 and NTCP colocalization across microtubule filaments, and a co-immunoprecipitation study showed that KIF4 physically binds to NTCP. KIF4 expression is regulated by FOXM1. Interestingly, we discovered that RXR agonists (Bexarotene, and Alitretinoin) down-regulated KIF4 expression via FOXM1-mediated suppression, resulting in a substantial decrease in HBV-Pre-S1 protein attachment to HepG2-hNTCP cell surface and subsequent suppression of HBV infection in HepG2-hNTCP and primary human hepatocytes (PXB) (Bexarotene, IC501.89 ± 0.98 μM). Overall, our findings show that human KIF4 is a critical regulator of NTCP surface transport and localization, which is required for NTCP to function as a receptor for HBV/HDV entry. Furthermore, small molecules that suppress or alleviate KIF4 expression would be potential antiviral candidates that target HBV and HDV entry phases.

Author Summary

Understanding HBV/HDV entry machinery and the mechanism by which NTCP (HBV/HDV entry receptor) surface expression is regulated is crucial to develop antiviral entry inhibitors. We found that NTCP surface transport is mainly controlled by the motor kinesin KIF4. Surprisingly, KIF4 was negatively regulated by RXR receptors through FOXM1-mediated suppression

This study not only mechanistically correlated the role of RXR receptors in regulating HBV/HDV entry but also suggested a novel approach to develop therapeutic rexinoids for preventing HBV and/or HDV infections in important clinical situations, such as in patients undergoing liver transplantation or those who are at a high risk of HBV infection and unresponsive to HBV vaccination.
Understanding the relationship between dispersal and range size
Authors: Alzate Adriana , Onstein Renske E.
Published: October 2021

Understanding what drives the vast variability in species range size is still an outstanding question. Among the several processes potentially affecting species ranges, dispersal is one of the most prominent hypothesized predictors. However, the theoretical expectation of a positive dispersal-range size relationship has received mixed empirical support. Here, we synthesized results from 84 studies to investigate in which context dispersal is most important in driving species range size. We found that dispersal traits – proxies for dispersal ability – explain range sizes more often in temperate and subtropical regions than in tropical regions, when considering multiple components of dispersal, and when investigating a large number of species to capture dispersal and range size variation. In plants, positive effects of dispersal on range size were less often detected when examining broad taxonomic levels. In animals, dispersal is more important for range size increase in ectotherms than in endotherms. Our synthesis emphasizes the importance of considering different aspects of the dispersal process -departure, transfer, settlement-, niche aspects and evolutionary components, like time for range expansion and past geological-environmental dynamics. We therefore call for a more integrative view of the dispersal process and its causal relationship with range size.
Characterization of morpho-functional traits in mesophotic corals reveals optimized light capture and photosynthesis
Authors: Kramer Netanel , Guan Jiaao , Chen Shaochen , Wangpraseurt Daniel , Loya Yossi
Published: October 2021

The morphology and skeleton architecture of photosynthetic corals modulates the light capture and functioning of the coral-algal symbiosis on shallow-water corals. Since corals can thrive on mesophotic reefs under extreme light-limited conditions, we hypothesized that microskeletal coral features optimize light capture under low-light environments. Using micro-computed tomography scanning, we conducted a comprehensive three-dimensional (3D) assessment of small-scale skeleton morphology of the depth-generalist coral Stylophora pistillata collected from shallow (5 m) and mesophotic (45 m) depths. We detected a high phenotypic diversity between depths, resulting in two distinct morphotypes, with calyx diameter, theca height, and corallite marginal spacing contributing to most of the variation between depths. To determine whether such depth-specific morphotypes affect coral light capture and photosynthesis on the corallite-scale, we developed 3D simulations of light propagation based on photosynthesis-irradiance parameters. We found that corals associated with shallow morphotypes dissipated excess light through self-shading microskeletal features; while mesophotic morphotypes facilitated enhanced light absorption and photosynthesis under low-light conditions. We conclude that the mesophotic coral architecture provides a greater ability to trap solar energy and efficiently exploit the limited light conditions, and suggest that morphological modifications play a key role in the photoadaptation response to low-light.
Coral assemblages at higher latitudes favour short-term potential over long-term performance
Authors: Cant James , Reimer James D. , Sommer Brigitte , Cook Katie M. , Kim Sun W. , Sims Carrie A. , Mezaki Takuma , O’Flaherty Cliodhna , Brooks Maxime , Malcolm Hamish A. , Pandolfi John M. , Salguero-Gómez Roberto , Beger Maria
Published: October 2021

The persistent exposure of coral communities to more variable abiotic regimes is assumed to augment their resilience to future climatic variability. Yet, while the determinants of coral population resilience across species remain unknown, we are unable to predict the winners and losers across reef ecosystems exposed to increasingly variable conditions. Using annual surveys of 3171 coral individuals across Australia and Japan (2017-2019), we explore spatial variation across the short- and long-term dynamics of competitive, stress-tolerant, and weedy assemblages to evaluate how thermal variability mediates the structural composition of coral communities. We illustrate how, by promoting short-term potential over long-term performance, coral assemblages can reduce their vulnerability to stochastic environments. However, compared to stress-tolerant, and weedy assemblages, competitive coral taxa display a reduced capacity for elevating their short-term potential. Accordingly, future climatic shifts threaten the structural complexity of coral assemblages in variable environments, emulating the degradation expected across global tropical reefs.
Recombinant Fsh and Lh therapy for spawning induction of previtellogenic and early spermatogenic arrested teleost, the flathead grey mullet (Mugil cephalus)
Authors: Ramos-Júdez Sandra , Giménez Ignacio , Gumbau-Pous Josep , Arnold-Cruañes Lucas Stephen , Estévez Alicia , Duncan Neil
Published: October 2021

With the expansion and diversification of global aquaculture, efforts continue to develop new bio-technologies for assisted reproduction in species that present reproductive dysfunctions. Flathead grey mullet (Mugil cephalus) held in intensive conditions in the Mediterranean region, display a severe reproductive dysfunction, where males do not produce fluent milt and females are arrested at previtellogenesis or early stages of vitellogenesis. In the present study, weekly injections of species-specific single-chain recombinant gonadotropins (rGths); follicle stimulating hormone (rFsh) (6 to 12 μg kg-1 doses) and luteinizing hormone (rLh) (2.5 to 24 μg kg-1 doses) were administered to induce vitellogenesis, from previtellogenesis / early vitellogenesis to the completion of vitellogenic growth in females and enhance spermatogenesis to produce adequate volumes of sperm from non-fluent males. During the experiment, all treated females (n = 21) developed oocytes in late vitellogenesis with 603 ± 8 μm diameter and all treated males produced fluent sperm. To induce oocyte maturation, ovulation and spawning, females were treated with either (i) a priming dose of 30 μg kg-1 of rLh and a resolving dose of 40 mg kg-1 of progesterone (P4), (ii) priming and resolving doses of 30 μg kg-1 of rLh, or (iii) priming and resolving doses of 40 mg kg-1 of P4 given 24:05 ± 0:40 h apart. Females were placed in spawning tanks with rGth treated males that had fluent sperm. Spontaneous spawns of fertilised eggs were obtained after inducing with rLh + P4 or rLh + rLh (priming and resolving injections) with a spawning success of the 85% (8 of 9 females) and 100% (n = 6), respectively. The eggs collected from the tanks presented 64 ± 22% fertilization with embryo development and 57 ± 24 % hatching. The treatment P4 + P4 had a lower ovulation success (50 % - 3 of 6 females) and spawning success (17 %) with no fertilised eggs. Success was independent of the initial gonadal stage of females. In comparison, control females did not show any advance in gonadal development from initial stages and control males did not produce fluent sperm. The present results confirm the possibility of controlling oogenesis from previtellogenesis to the completion of maturation and fertilised tank spawning using exclusively rFsh and rLh in a teleost species.
SHAPR predicts 3D cell shapes from 2D microscopic images
Authors: Waibel Dominik J. E. , Kiermeyer Niklas , Atwell Scott , Sadafi Ario , Meier Matthias , Marr Carsten
Published: October 2021

Reconstruction of shapes and sizes of three-dimensional (3D) objects from two-dimensional (2D) information is an intensely studied subject in computer vision. We here consider the level of single cells and nuclei and present a neural network-based SHApe PRediction autoencoder. For proof-of-concept, SHAPR reconstructs 3D shapes of red blood cells from single view 2D confocal microscopy images more accurately than naïve stereological models and significantly increases the feature-based prediction of red blood cell types from F1 = 79.0% to F1 = 87.4%. Applied to 2D images containing spheroidal aggregates of densely grown human induced pluripotent stem cells, we find that SHAPR learns fundamental shape properties of cell nuclei and allows for prediction-based morphometry. Reducing imaging time and data storage, SHAPR will help to optimize and up-scale image-based high-throughput applications for biomedicine.
Multi-omics and deep learning provide a multifaceted view of cancer
Authors: Uyar Bora , Ronen Jonathan , Franke Vedran , Gargiulo Gaetano , Akalin Altuna
Published: October 2021

Cancer is a complex disease with a large financial and healthcare burden on society. One hallmark of the disease is the uncontrolled growth and proliferation of malignant cells. Unlike Mendelian diseases which may be explained by a few genomic loci, a deeper molecular and mechanistic understanding of the development of cancer is needed. Such an endeavor requires the integration of tens of thousands of molecular features across multiple layers of information encoded in the cells. In practical terms, this implies integration of multi omics information from the genome, transcriptome, epigenome, proteome, metabolome, and even micro-environmental factors such as the microbiome. Finding mechanistic insights and biomarkers in such a high dimensional space is a challenging task. Therefore, efficient machine learning techniques are needed to reduce the dimensionality of the data while simultaneously discovering complex but meaningful biomarkers. These markers then can lead to testable hypotheses in research and clinical applications. In this study, we applied advanced deep learning methods to uncover multi-omic fingerprints that are associated with a wide range of clinical and molecular features of tumor samples. Using these fingerprints, we can accurately classify different cancer types, and their subtypes. Non-linear multi-omic fingerprints can uncover clinical features associated with patient survival and response to treatment, ranging from chemotherapy to immunotherapy. In addition, multi-omic fingerprints may be deconvoluted into a meaningful subset of genes and genomic alterations to support clinically relevant decisions.

Graphical Abstract
Human disturbances erode the diversity of species resilience strategies
Authors: Merrien Thomas , Davis Katrina J , Di Marco Moreno , Capdevila Pol , Salguero-Gómez Roberto
Published: October 2021

Human activities are drastically reshaping Earth’s ecosystems. Across the tree of life, species become threatened and ultimately go extinct when they are unable to cope with these changes. Hence, understanding the resilience of natural populations is necessary to understand and predict species’ capacity to cope with increasing human pressures. Here, we use high-resolution demographic information for 921 populations of wild plants and animals to assess how they respond to increasing levels of human pressure. We show that fewer successful resilience strategies, allowing population to persist in disturb environments, exist in human-influenced habitats compared to pristine habitats. In contrast, pristine habitats host species with higher resistance and faster recovery than more altered environments. Importantly, the examined macroecologial patterns of demographic resilience are kingdom- and mobility-specific: natural populations of plants recover faster and have a propensity to grow faster after a disturbance (i.e., compensation) in urban areas than in pristine habitats, while these tendencies do not appear in animals. Likewise, populations of animals with limited mobility are less able to resist or compensate for disturbances in human altered environments than highly mobile populations. Our results suggest that human activities have eroded the diversity of natural populations’ resilience strategies. This finding implies that species will be less tolerant to disturbance in the future, as continuing biodiversity loss and increasing human impacts will ultimately shrink the spectrum of resilience strategies of organisms.