bluuebunny/crossref_metadata_2025_split huggingface dataset:
First genetic data for the Critically Endangered Cuban endemic Zapata RailCyanolimnas cerverai, and the taxonomic implications
Authors: Brown Alex F. , Shannon Thomas J. , Collinson J. Martin , Kirwan Guy M. , Kirkconnell Arturo , Stervander Martin 
Published: February 2022

ABSTRACTThe taxonomic affinity of the near-flightless Zapata RailCyanolimnas cerverai, a Critically Endangered and highly localized species endemic to Cuba, has long been debated. Morphological analyses have suggested that this species, which constitutes a monotypic genus, could be related either to the extinct Tahitian Cave Rails (Nesotrochissp.) or to the South American rail tribe Pardirallini, i.e., the generaNeocrex, Mustelirallus, andPardirallus. Whilst pronounced phenotypic convergence–and divergence–among rails have repeatedly proven morphology-based phylogenies unreliable, thus far no attempt to sequence DNA from the enigmaticCyanolimnashas succeeded. In this study, we extracted historic DNA from a museum specimen collected in 1927 and sequenced multiple short fragments that allowed us to assemble a partial sequence of the mitochondrial cytochrome oxidase I gene. Phylogenetic analyses confirm thatCyanolimnasbelongs in tribe Pardirallini as sister to genusNeocrex, from which it diverged about six million years ago. Their divergence fromMusteliralluswas estimated at about eight million years ago. Based on morphology and our mitochondrial phylogeny, we conclude that it is unjustified to retain the monotypic genusCyanolimnasand tentatively recommend thatC. cerveraiand the twoNeocrexspecies are ascribed to genusMustelirallus.Abstract Figure
Using cGMP analogues to modulate photoreceptor light sensitivity: Perspectives for the treatment of retinal degeneration
Authors: Wucherpfennig Sophie , Haq Wadood , Popp Valerie , Kesh Sandeep , Das Soumyaparna , Melle Christian , Rentsch Andreas , Schwede Frank , Paquet-Durand François , Nache Vasilica 
Published: February 2022

AbstractCyclic nucleotide-gated (CNG) channels play an essential role within the phototransduction cascade in vertebrates. Although rod and cone light responses are mediated through similar pathways, each photoreceptor type relies on a specific CNG-channel isoform. In many forms of retinal degeneration, increased cGMP levels initiate a pathophysiological rollercoaster, which starts with an enhanced CNG-channel activation, often in rod photoreceptors. This causes cell death of both rods and cones, and eventually leads to complete blindness. Unfortunately, the targeting of the desired channel isoform still constitutes the bottleneck for many therapeutic schemes.Here, we present a novel strategy, based on cGMP analogues with opposite types of action, which allows for the selective modulation of either rod or cone photoreceptors. A combined treatment with a weak rod-selective CNG-channel inhibitor (Rp-8-Br-PET-cGMPS) and a cone-selective CNG-channel activator (8-pCPT-cGMP) preserved the normal CNG-channel function at physiological and pathological cGMP levels. The effectiveness of this approach was tested and confirmed in explanted mouse retina. Under physiological conditions, the inhibitor silenced the rods selectively and decreased the dependency of cone responses on light intensity. Remarkably, the activator, when applied together with the inhibitor, reinstated only the light responsiveness of cones. Yet, when applied alone, the activator dampened rod responses more strongly than those of cones.Hence, combinations of cGMP analogues with desired properties may elegantly address the isoform-specificity problem in future pharmacological therapies. Beyond therapies for retinal degeneration diseases, treatments based on this strategy may allow modulation of visual performance in certain light environments or disease conditions.One Sentence SummaryA combination of cGMP analogues with opposite types of action can selectively modulate either rod or cone photoreceptor function.
Systematic Single Cell Pathway Analysis (SCPA) reveals novel pathways engaged during early T cell activation
Authors: Bibby Jack A. , Agarwal Divyansh , Freiwald Tilo , Kunz Natalia , Merle Nicolas S. , West Erin E. , Larochelle Andre , Chinian Fariba , Mukherjee Somabha , Afzali Behdad , Kemper Claudia , Zhang Nancy R. 
Published: February 2022

SummaryNext generation sequencing technologies have revolutionized the study of T cell biology, capturing previously unrecognized diversity in cellular states and functions. Pathway analysis is a key analytical stage in the interpretation of such transcriptomic data, providing a powerful method for detecting alterations in important biological processes. Current pathway analysis tools are built on models developed for bulk-RNA sequencing, limiting their effectiveness when applied to more complex single cell RNA-sequencing (scRNA-seq) datasets. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package Single Cell Pathway Analysis (SCPA). After demonstrating the effectiveness of SCPA over commonly used methods, we generate a scRNA-seq T cell dataset and characterize pathway activity over early cellular activation and between T cell populations. This revealed unexpected regulatory pathways in T cells, such as an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems level characterization of pathway activity in T cells across multiple human tissues also revealed alpha defensin expression as a hallmark of bone marrow derived T cells. Overall, our work here provides a widely applicable tool for single cell pathway analysis, and highlights unexpected regulatory mechanisms of T cells using a novel T cell dataset.
Transient oscillations of neural firing rate associated with routing of evidence in a perceptual decision
Authors: Odean Naomi N , Sanayei Mehdi , Shadlen Michael N 
Published: February 2022

AbstractTo form a perceptual decision the brain must acquire samples of evidence from the environment and incorporate them in computations that mediate choice behavior. While much is known about the neural circuits that process sensory information and those that form decisions, less is known about the mechanisms that establish the functional linkage between them. We trained monkeys to make difficult decisions about the net direction of visual motion under conditions that required trial-by-trial control of functional connectivity. In one condition, the motion appeared at different locations on different trials. In the other, two motion patches appeared, only one of which was informative. Neurons in the parietal cortex produced brief oscillations in their firing rate at the time routing was established: upon onset of the motion display when its location was unpredictable across trials, and upon onset of an attention cue that indicated in which of two locations an informative patch of dots would appear. The oscillation was absent when the stimulus location was fixed across trials. We interpret the oscillation as a manifestation of the mechanism that establishes the source and destination of flexibly routed information, but not the transmission of the information per se.
Genome-wide analysis and evolutionary history of the Necrosis and Ethylene-inducing peptide 1-like protein (NLP) superfamily across the Dothideomycetes class of fungi
Authors: Dal’Sasso Thaís C. S. , Rody Hugo V. S. , Oliveira Luiz O. 
Published: February 2022

AbstractNecrosis and Ethylene-inducing peptide 1-like proteins (NLPs) are broadly distributed across bacteria, fungi and oomycetes. Cytotoxic NLPs are usually secreted into the host apoplast where they can induce cell death and trigger plant immune responses in eudicots. To investigate the evolutionary history of the NLPs, we accessed the genomic resources of 79 species from 15 orders of Dothideomycetes. Phylogenetic approaches searched for biased patterns of NLP gene evolution and aimed to provide a phylogenetic framework for the cytotoxic activities of NLPs. Among Dothideomycetes, the NLP superfamily sizes varied, but usually contained from one to six members. Superfamily sizes were higher among pathogenic fungi, with family members that were mostly effector NLPs. Across species, members of the NLP1 family (Type I NLPs) were predominant (84%) over members of the NLP2 family (Type II NLPs). The NLP1 family split into two subfamilies (NLP1.1 and NLP1.2). The NLP1.1 subfamily was broadly distributed across Dothideomycetes. There was strong agreement between the phylogenomics of Dothideomycetes and the phylogenetic tree based on members of the NLP1 subfamilies. To a lesser extent, phylogenomics also agreed with the phylogeny based on members of the NLP2 family. While gene losses seem to have shaped the evolutionary history of NLP2 family, ancient gene duplications followed by descent with modification characterized the NLP1 family. The strongest cytotoxic activities were recorded on NLPs of the NLP1.1 subfamily, suggesting that biased NLP gene retention in this subfamily favored the cytotoxic paralogs.
iDESC: Identifying differential expression in single-cell RNA sequencing data with multiple subjects
Authors: Liu Yunqing , Wang Ningya , Adams Taylor S. , Schupp Jonas C. , Wu Weimiao , McDonough John E. , Chupp Geoffrey L. , Kaminski Naftali , Wang Zuoheng , Yan Xiting 
Published: February 2022

AbstractSingle-cell RNA sequencing (scRNA-seq) enables assessment of transcriptome-wide changes at single-cell resolution. However, dominant subject effect in scRNA-seq datasets with multiple subjects severely confounds cell-type-specific differential expression (DE) analysis. We developed iDESC to separate subject effect from disease effect with consideration of dropouts to identify DE genes. iDESC was shown to have well-controlled type I error and high power compared to existing methods and obtained the best consistency between datasets and disease relevance in two scRNA-seq datasets from same disease, suggesting the importance of considering subject effect and dropouts in the DE analysis of scRNA-seq data with multiple subjects.
Haplotype-enhanced inference of somatic copy number profiles from single-cell transcriptomes
Authors: Gao Teng , Soldatov Ruslan , Sarkar Hirak , Kurkiewicz Adam , Biederstedt Evan , Loh Po-Ru , Kharchenko Peter 
Published: February 2022

AbstractGenome instability and aberrant alterations of transcriptional programs both play important roles in cancer. However, their relationship and relative contribution to tumor evolution and therapy resistance are not well-understood. Single-cell RNA sequencing (scRNA-seq) has the potential to investigate both genetic and non-genetic sources of tumor heterogeneity in a single assay. Here we present a computational method, Numbat, that integrates haplotype information obtained from population-based phasing with allele and expression signals to enhance detection of CNVs from scRNA-seq data. To resolve tumor clonal architecture, Numbat exploits the evolutionary relationships between subclones to iteratively infer the single-cell copy number profiles and tumor clonal phylogeny. Analyzing 21 tumor samples composed of multiple myeloma, breast, and thyroid cancers, we show that Numbat can accurately reconstruct the tumor copy number profile and precisely identify malignant cells in the tumor microenvironment. We uncover additional subclonal complexity contributed by allele-specific alterations, and identify genetic subpopulations with transcriptional signatures relevant to tumor progression and therapy resistance. We hope that the increased power to characterize genomic aberrations and tumor subclonal phylogenies provided by Numbat will help delineate contributions of genetic and non-genetic mechanisms in cancer.
Converging pathways found in copy number variation syndromes with high schizophrenia risk
Authors: Ehrhart Friederike , Silva Ana , van Amelsvoort Therese , von Scheibler Emma , Evelo Chris , Linden David E.J. 
Published: February 2022

AbstractSchizophrenia genetics is complex, and the contribution of common and rare variants are not fully understood. Several specific copy number variations (CNVs) confer increased risk for schizophrenia, and the study of their effects is central to molecular models of mental illness. However, these CNVs – microdeletions or -duplications – are spread across the genome and differ in the number of genes affected and classes of coded proteins. This suggests that, in order to fully understand the contribution of these genetic variants to mental illness, we need to look beyond the deleted or duplicated genes, to their interaction partners and involved molecular pathways.In this study, we developed machine-readable interactive pathways to enable analysis of downstream effects of genes within CNV loci and identify common pathways between CNVs with high schizophrenia risk using the WikiPathways database, and schizophrenia risk gene collections from GWAS studies and a gene-disease association database. For CNVs that are pathogenic for schizophrenia, we found overlapping pathways, including BDNF signaling, cytoskeleton, cell-cell connections, inflammation and MAPK3 signaling. Common schizophrenia risk genes identified by different studies are found in all CNV pathways but not enriched.Our findings suggest that specific pathways – such as BDNF signaling – may be critical contributors to schizophrenia risk conferred by rare CNVs, and common risk variants may operate through distinct mechanisms. Our approach also highlights the importance of not only investigating deleted or duplicated genes within pathogenic CNV loci, but also study their direct interaction partners, which may explain pleiotropic effects of CNVs on schizophrenia risk.
Landscape functional connectivity for butterflies under different scenarios of land-use, land-cover, and climate change in Australia
Authors: Diengdoh Vishesh L. , Ondei Stefania , Amin Rahil J. , Hunt Mark , Brook Barry W. 
Published: February 2022

AbstractPollinating invertebrates are vital to terrestrial ecosystems but are impacted by anthropogenic habitat loss/fragmentation and climate change. Conserving and improving landscape connectivity is important to offset those threats, yet its assessment for invertebrates is lacking. In this study, we evaluated the functional connectivity between protected areas in Australia for 59 butterfly species, under present conditions and different future scenarios (for 2050 and 2090) of land-use, land-cover, and climate change. Using circuit-theory analysis, we found that functional connectivity under present conditions varies widely between species, even when their estimated geographical ranges are similar. Under future scenarios, functional connectivity is predicted to decrease overall, with negative changes worsening from 2050 to 2090, although a few species are positive exceptions. We have made our results available as spatial datasets to allow comparisons with taxa from other studies and can be used to identify priority areas for conservation in terms of establishing ecological corridors or stepping-stone habitat patches. Our study highlights the importance of considering pollinating invertebrates when seeking holistic conservation and restoration of a landscape’s functional connectivity, underscoring the need to expand and promote protected areas to facilitate functional connectivity under future scenarios of global change.Research DataThe habitat suitability maps and functional connectivity maps are made available as GeoTiff images via Figshare (10.6084/m9.figshare.19130078).
An Analysis of Protein Language Model Embeddings for Fold Prediction
Authors: Villegas-Morcillo Amelia , Gomez Angel M. , Sanchez Victoria 
Published: February 2022

AbstractThe identification of the protein fold class is a challenging problem in structural biology. Recent computational methods for fold prediction leverage deep learning techniques to extract protein fold-representative embeddings mainly using evolutionary information in the form of multiple sequence alignment (MSA) as input source. In contrast, protein language models (LM) have reshaped the field thanks to their ability to learn efficient protein representations (protein-LM embeddings) from purely sequential information in a self-supervised manner. In this paper, we analyze a framework for protein fold prediction using pre-trained protein-LM embeddings as input to several fine-tuning neural network models which are supervisedly trained with fold labels. In particular, we compare the performance of six protein-LM embeddings: the LSTM-based UniRep and SeqVec, and the transformer-based ESM-1b, ESM-MSA, ProtBERT, and ProtT5; as well as three neural networks: Multi-Layer Perceptron (MLP), ResCNN-BGRU (RBG), and Light-Attention (LAT). We separately evaluated the pairwise fold recognition (PFR) and direct fold classification (DFC) tasks on well-known benchmark datasets. The results indicate that the combination of transformer-based embeddings, particularly those obtained at amino acid-level, with the RBG and LAT fine-tuning models performs remarkably well in both tasks. To further increase prediction accuracy, we propose several ensemble strategies for PFR and DFC, which provide a significant performance boost over the current state-of-the-art results. All this suggests that moving from traditional protein representations to protein-LM embeddings is a very promising approach to protein fold-related tasks.
Fine-Tuning Transformers For Genomic Tasks
Authors: Martinek Vlastimil , Cechak David , Gresova Katarina , Alexiou Panagiotis , Simecek Petr 
Published: February 2022

AbstractTransformers are a type of neural network architecture that has been successfully used to achieve state-of-the-art performance in numerous natural language processing tasks. However, what about DNA, the language life written in the four-letter alphabet? In this paper, we review the current state of Transformers usage in genomics and molecular biology in general, introduce a collection of benchmark datasets for the classification of genomic sequences, and compare the performance of several model architectures on those benchmarks, including a BERT-like model for DNA sequences DNABERT as implemented in HuggingFace (armheb/DNA_bert_6 model). In particular, we explore the effect of pre-training on a large DNA corpus vs training from scratch (with randomized weights). The results presented here can be used for identification of functional elements in human and other genomes.
Latitudinal gradient in species diversity provides high niche opportunities for a range-expanding phytophagous insect
Authors: Jones Dylan G. , Kobelt Julia , Ross Jenna M. , Powell Thomas H.Q. , Prior Kirsten M. 
Published: February 2022

AbstractWhen species undergo poleward range expansions in response to anthropogenic change, they likely encounter less diverse communities in new locations. If low diversity communities provide weak biotic interactions, such as reduced competition for resources or predation, range-expanding species may experience ‘high niche opportunities.’Here, we uncover if oak gall wasp communities experience a latitudinal diversity gradient (LDG) and weaker interactions at the poles that might create high niche opportunities for a range-expanding community member.We performed systematic surveys of oak gall wasps on a dominant oak, Quercus garryana, throughout most of its range, from northern California to Vancouver Island, British Columbia. On 540 trees at 18 sites, we identified 23 species in three guilds (leaf detachable, leaf integral, and stem galls). We performed regressions between oak gall wasp diversity, latitude, and other abiotic and habitat factors to reveal if cynipid communities follow an LDG. To uncover patterns in local interactions, we performed partial correlations on oak gall wasps co-occurring on trees within regions. Finally, we performed regressions between abundances of co-occurring gall wasps on trees to reveal potential interactions.Q. garryana-gall wasp communities followed an LDG, with lower diversity at higher latitudes, particularly with a loss of detachable leaf gall species. Detachable leaf gall wasps, including the range-expanding species, co-occurred most on trees and had weak interactions in the northern region. Abundances of the range-expander and detachable and integral leaf galls co-occurring on trees were negatively related, suggesting antagonistic interactions. Overall, we found that LDGs create communities with weaker antagonistic interactions at the poles that might facilitate ecological release in a range-expanding community member.Here, we uncover how regional and local scale patterns and processes create high niche opportunities for a range-expanding community member. This research provides insight into how biogeographical patterns in communities and species interactions influence the outcome of range expansions. Given the ubiquity of LDGs, these outcomes might be expected in other phytophagous insect communities.
Longitudinal examination of perfusion and angiogenesis markers in primary colorectal tumors shows distinct signatures for metronomic and maximum-tolerated dose strategies
Authors: Mundo Ariel I. , Muhammad Abdussaboor , Balza Kerlin , Nelson Christopher E. , Muldoon Timothy J. 
Published: February 2022

1AbstractMetronomic chemotherapy (MET) has been developed to address the shortcomings of maximum-tolerated chemotherapy (MTD) in regard to toxicity and development of resistance mechanisms in the tumor. In colorectal cancer (CRC), MET is a promising novel strategy to treat locally advanced malignancies when used as neoadjuvant chemotherapy (NAC). However, so far there are no preclinical studies to assess the impact of MET NAC in CRC to assess the benefits and challenges of this approach. Here, we used a primary model of CRC (via azoxymethane) to analyze longitudinal changes in angiogenesis in primary tumors under MET and MTD NAC using a combination of diffuse reflectance spectroscopy and mRNA expression (via qPCR). Our results show that MET and MTD NAC lead to increased mean tissue oxygen saturation (8% and 5%, respectively) and oxyhemoglobin (15% and 10%) between weeks 2 and 5 of NAC, and that such increases are caused by distinct molecular signatures in the angiogenic program. Specifically, we find that in the MET group there is a sustained increase in Hif-1a, Aldoa, and Pgk1 expression, suggesting upregulated glycolysis, whereas MTD NAC causes a significant reduction in the expression of the aforementioned genes and of Vegf, leading to vascular remodeling in MTD-treated tumors. Taken together, this study demonstrates the ability of combined optical and molecular methodologies to provide a holistic picture of tumor response to therapy in CRC in a minimally invasive manner.
Tree of Mutually Exclusive Oncogenes
Authors: Neyshabouri Mohammadreza Mohaghegh , Lagergren Jens 
Published: February 2022

AbstractIdentifying cancer driver genes and their interrelations is critical in understanding cancer progression mechanisms. In this paper, we introduce ToMExO, a probabilistic method to infer cancer driver genes and how they affect each other, using cross-sectional data from cohorts of tumors. We model cancer progression dynamics using a tree with sets of driver genes in the nodes. This model explains the temporal orders among driver mutations and their mutual exclusivity patterns. We introduce a dynamic programming procedure for the likelihood calculation and build an MCMC inference algorithm. Together with our engineered MCMC moves, our efficient likelihood calculations enable us to work with datasets having hundreds of genes and thousands of tumors in the datasets. We demonstrate our method’s performance on several synthetic datasets covering various scenarios for cancer progression dynamics. We then present the analyses of several biological datasets using the ToMExO method and validate the results using a set of method-independent metrics.