bluuebunny/crossref_metadata_2025_split huggingface dataset:
Semi-supervised single-cell cross-modality translation using Polarbear
Authors: Zhang Ran , Meng-Papaxanthos Laetitia , Vert Jean-Philippe , Noble William Stafford 
Published: November 2021

AbstractThe emergence of single-cell co-assays enables us to learn to translate between single-cell modalities, potentially offering valuable insights from datasets where only one modality is available. However, the sparsity of single-cell measurements and the limited number of cells measured in typical co-assay datasets impedes the power of cross-modality translation. Here, we propose Polarbear, a semi-supervised translation framework to predict cross-modality profiles that is trained using a combination of co-assay data and traditional “single-assay” data. Polarbear uses single-assay and co-assay data to train an autoencoder for each modality and then uses just the co-assay data to train a translator between the embedded representations learned by the autoencoders. With this approach, Polarbear is able to translate between modalities with improved accuracy relative to state-of-the-art translation techniques. As an added benefit of the training procedure, we show that Polarbear also produces a matching of cells across modalities.
Slow fluctuations in ongoing brain activity decrease in amplitude with ageing yet their impact on task-related evoked responses is dissociable from behaviour
Authors: Ribeiro Maria J. , Castelo-Branco Miguel 
Published: November 2021

AbstractIn humans, ageing is characterized by decreased brain signal variability and increased behavioural variability. To understand how reduced brain variability segregates with increased behavioural variability, we investigated the association between reaction time variability, evoked brain responses and ongoing brain signal dynamics, in young (N = 36) and older adults (N = 39). We studied the electroencephalogram (EEG) and pupil size fluctuations to characterize the cortical and arousal responses elicited by a cued go/no-go task. Evoked responses were strongly modulated by slow (< 2 Hz) fluctuations of the ongoing signals, which presented reduced power in the older participants. Although variability of the evoked responses was lower in the older participants, once we adjusted for the effect of the ongoing signal fluctuations, evoked responses were equally variable in both groups. Moreover, the modulation of the evoked responses caused by the ongoing signal fluctuations had no impact on reaction time, thereby explaining why although ongoing brain signal variability is decreased in older individuals, behavioural variability is not. Finally, we showed that adjusting for the effect of the ongoing signal was critical to unmask the link between neural responses and behaviour.
A non-transcriptional function of Yap orchestrates the DNA replication program
Authors: García Rodrigo Meléndez , Haccard Olivier , Chesneau Albert , Narassimprakash Hemalatha , Roger Jérôme E , Perron Muriel , Marheineke Kathrin , Bronchain Odile 
Published: November 2021

AbstractIn multicellular eukaryotic organisms, the initiation of DNA replication occurs asynchronously throughout S-phase according to a regulated replication timing program. Here, using Xenopus egg extracts, we showed that Yap (Yes-associated protein 1), a downstream effector of the Hippo signaling pathway, is required for the control of DNA replication dynamics. We found that Yap is recruited to chromatin at the start of DNA replication and that Yap depletion accelerates DNA replication dynamics by increasing the number of activated replication origins. Furthermore, we identified Rif1, a major regulator of the DNA replication timing program, as a novel Yap binding protein. In Xenopus embryos, using a Trim-Away approach during cleavage stages devoid of transcription, we found that both Yap and Rif1 depletion trigger an acceleration of cell divisions, suggesting a shorter S-phase by alterations of the replication program. Finally, our data show that Rif1 knockdown leads to defects in the partitioning of early versus late replication foci in retinal stem cells, as we previously showed for Yap. Altogether, our findings unveil a non-transcriptional role for Yap in regulating replication dynamics. We propose that Yap and Rif1 function as breaks to control the DNA replication program in early embryos and post-embryonic stem cells.HighlightsYap is recruited to chromatin during DNA replication dependent on pre-replicative complex assembly.Yap controls DNA replication dynamics by limiting origin firing.The replication timing regulatory factor 1, Rif1, is a novel Yap binding-partner.Both Yap and Rif1 regulate the length of the first embryonic cell cycles.Like Yap, Rif1 controls retinal stem cell DNA replication timing.
Historical specimens and the limits of subspecies phylogenomics in the New World quails (Odontophoridae)
Authors: Salter Jessie F. , Hosner Peter A. , Tsai Whitney L. E. , McCormack John E. , Braun Edward L. , Kimball Rebecca T. , Brumfield Robb T. , Faircloth Brant C. 
Published: November 2021

AbstractAs phylogenomics focuses on comprehensive taxon sampling at the species and population/subspecies levels, incorporating genomic data from historical specimens has become increasingly common. While historical samples can fill critical gaps in our understanding of the evolutionary history of diverse groups, they also introduce additional sources of phylogenomic uncertainty, making it difficult to discern novel evolutionary relationships from artifacts caused by sample quality issues. These problems highlight the need for improved strategies to disentangle artifactual patterns from true biological signal as historical specimens become more prevalent in phylogenomic datasets. Here, we tested the limits of historical specimen-driven phylogenomics to resolve subspecies-level relationships within a highly polytypic family, the New World quails (Odontophoridae), using thousands of ultraconserved elements (UCEs). We found that relationships at and above the species-level were well-resolved and highly supported across all analyses, with the exception of discordant relationships within the two most polytypic genera which included many historical specimens. We examined the causes of discordance and found that inferring phylogenies from subsets of taxa resolved the disagreements, suggesting that analyzing subclades can help remove artifactual causes of discordance in datasets that include historical samples. At the subspecies-level, we found well-resolved geographic structure within the two most polytypic genera, including the most polytypic species in this family, Northern Bobwhites (Colinus virginianus), demonstrating that variable sites within UCEs are capable of resolving phylogenetic structure below the species level. Our results highlight the importance of complete taxonomic sampling for resolving relationships among polytypic species, often through the inclusion of historical specimens, and we propose an integrative strategy for understanding and addressing the uncertainty that historical samples sometimes introduce to phylogenetic analyses.
Filtration extraction method using microfluidic channel for measuring environmental DNA
Authors: Fukuzawa Takashi , Kameda Yuichi , Nagata Hisao , Nishizawa Naofumi , Doi Hideyuki 
Published: November 2021

AbstractThe environmental DNA (eDNA) method, which is widely applied for biomonitoring, is limited to laboratory analysis and processing. In this study, we developed a filtration/extraction component using a microfluidic channel, Biryu-Chip (BC), and a filtration/extraction method, BC method, to minimize the volume of the sample necessary for DNA extraction and subsequent PCR amplification. We tested the performance of the BC method and compared it with the Sterivex filtration/extraction method using aquarium and river water samples. We observed that using the BC method, the same concentration of the extracted DNA was obtained with 1/20–1/40 of the filtration volume of the Sterivex method, suggesting that the BC method can be widely used for eDNA measurement. In addition, we could perform on-site measurements of eDNA within 30 min using a mobile PCR device. Using the BC method, filtration and extraction could be performed easily and quickly. The PCR results obtained by the BC method were similar to those obtained by the Sterivex method. The BC method required fewer steps and therefore, the risk of DNA contamination could be reduced. When combined with a mobile PCR, the BC method can be applied to easily detect eDNA within 30 min from a few 10 mL of the water sample, even on-site.
Accuracy and data efficiency in deep learning models of protein expression
Authors: Nikolados Evangelos-Marios , Wongprommoon Arin , Mac Aodha Oisin , Cambray Guillaume , Oyarzún Diego A. 
Published: November 2021

AbstractMany applications of synthetic biology involve engineering microbial strains to express high-value proteins. Thanks to advances in rapid DNA synthesis and sequencing, deep learning has emerged as a promising approach to build sequence-to-expression models for strain design and optimization. Such models, however, require large amounts of training data that are costly to acquire, which creates substantial entry barriers for many laboratories. Here, we study the relation between model accuracy and data efficiency in a large panel of machine learning models of varied complexity, from penalized linear regressors to deep neural networks. Our analysis is based on data from a large genotype-phenotype screen inEscherichia coli, which was generated with a design-of-experiments approach to balance coverage and depth of the genotypic space. We sampled these data to emulate scenarios with a limited number of DNA sequences for training, as commonly encountered in strain engineering applications. Our results suggest that classic, non-deep, models can achieve good prediction accuracy with much smaller datasets than previously thought, and provide robust evidence that convolutional neural networks further improve performance with the same amount of data. Using methods from Explainable AI and model benchmarking, we show that convolutional neural networks have an improved ability to discriminate between input sequences and extract sequence features that are highly predictive of protein expression. We moreover show that controlled sequence diversity leads to important gains in data efficiency, and validated this principle in a separate genotype-phenotype screen inSaccharomyces cerevisiae.These results provide practitioners with guidelines for designing experimental screens that strike a balance between cost and quality of training data, laying the groundwork for wider adoption of deep learning across the biotechnology sector.
TIS Transformer: Remapping the Human Proteome Using Deep Learning
Authors: Clauwaert Jim , Gupta Ramneek , McVey Zahra , Menschaert Gerben 
Published: November 2021

AbstractThe correct mapping of the proteome is an important step towards advancing our understanding of biological systems and cellular mechanisms. Methods that provide better mappings can fuel important processes such as drug discovery and disease understanding. Currently, true determination of translation initiation sites is primarily achieved byin vivoexperiments. Here we propose TIS Transformer, a deep learning model for the determination of translation start sites solely utilizing the information embedded in the transcript nucleotide sequence. The method is built upon deep learning techniques first designed for natural language processing. We prove this approach to be best suited for learning the semantics of translation, outperforming previous approaches by a large margin. We demonstrate that limitations in the model performance is primarily due to the presence of low quality annotations against which the model is evaluated against. Advantages of the method are its ability to detect key features of the translation process and multiple coding sequences on a transcript. These include micropeptides encoded by short Open Reading Frames, either alongside a canonical coding sequence or within long non-coding RNAs. To demonstrate the use of our methods, we applied TIS Transformer to remap the full human proteome.
Earliest photic zone niches probed by ancestral microbial rhodopsins
Authors: Sephus Cathryn D. , Fer Evrim , Garcia Amanda K. , Adam Zachary R. , Schwieterman Edward W. , Kaçar Betül 
Published: November 2021

ABSTRACTFor billions of years, life has continuously adapted to dynamic physical conditions near the Earth’s surface. Fossils and other preserved biosignatures in the paleontological record are the most direct evidence for reconstructing the broad historical contours of this adaptive interplay. However, biosignatures dating to Earth’s earliest history are exceedingly rare. Here, we combine phylogenetic inference of primordial rhodopsin proteins with modeled spectral features of the Precambrian Earth environment to reconstruct the paleobiological history of this essential family of photoactive transmembrane proteins. Our results suggest that ancestral microbial rhodopsins likely acted as light-driven proton pumps and were spectrally tuned toward the absorption of green light, which would have enabled their hosts to occupy depths in a water column or biofilm where UV wavelengths were attenuated. Subsequent diversification of rhodopsin functions and peak absorption frequencies was enabled by the expansion of surface ecological niches induced by the accumulation of atmospheric oxygen. Inferred ancestors retain distinct associations between extant functions and peak absorption frequencies. Our findings suggest that novel information encoded by biomolecules can be used as “paleosensors” for conditions of ancient, inhabited niches of host organisms not represented elsewhere in the paleontological record. The coupling of functional diversification and spectral tuning of this taxonomically diverse protein family underscores the utility of rhodopsins as universal testbeds for inferring remotely detectable biosignatures on inhabited planetary bodies.
ZARP: An automated workflow for processing of RNA-seq data
Authors: Katsantoni Maria , Gypas Foivos , Herrmann Christina J. , Burri Dominik , Bak Maciej , Iborra Paula , Agarwal Krish , Ataman Meric , Börsch Anastasiya , Zavolan Mihaela , Kanitz Alexander 
Published: November 2021

AbstractRNA sequencing (RNA-seq) is a crucial technique for many scientific studies and multiple models, and software packages have been developed for the processing and analysis of such data. Given the plethora of available tools, choosing the most appropriate ones is a time-consuming process that requires an in-depth understanding of the data, as well as of the principles and parameters of each tool. In addition, packages designed for individual tasks are developed in different programming languages and have dependencies of various degrees of complexity, which renders their installation and execution challenging for users with limited computational expertise. The use of workflow languages and execution engines with support for virtualization and encapsulation options such as containers and Conda environments facilitates these tasks considerably. Computational workflows defined in those languages can be reliably shared with the scientific community, enhancing reusability, while improving reproducibility of results by making individual analysis steps more transparent.Here we present ZARP, a general purpose RNA-seq analysis workflow which builds on state-of-the-art software in the field to facilitate the analysis of RNA-seq data sets. ZARP is developed in the Snakemake workflow language using best software development practices. It can run locally or in a cluster environment, generating extensive reports not only of the data but also of the options utilized. It is built using modern technologies with the ultimate goal to reduce the hands-on time for bioinformaticians and non-expert users. ZARP is available under a permissive Open Source license and open to contributions by the scientific community.Contactmihaela.zavolan@unibas.ch, alexander.kanitz@unibas.ch
Epigenetic machinery is functionally conserved in cephalopods
Authors: Macchi Filippo , Edsinger Eric , Sadler Kirsten C. 
Published: November 2021

AbstractEpigenetic regulatory mechanisms are divergent across the animal kingdom, yet little is known about the epigenome in non-model organisms. Unique features of cephalopods make them attractive for investigating behavioral, sensory, developmental and regenerative processes, but using molecular approaches in such studies is hindered by the lack of knowledge about genome organization and gene regulation in these animals. We combined bioinformatic and molecular analysis of Octopus bimaculoides to identify gene expression signatures for 12 adult tissues and a hatchling, and investigate the presence and pattern of DNA methylation and histone methylation marks across tissues. This revealed a dynamic gene expression profile encoding several epigenetic regulators, including DNA methylation maintenance factors that were highly conserved and functional in cephalopods, as shown by detection of 5-methyl-cytosine in multiple tissues of octopus, squid and bobtail squid. WGBS of octopus brain and RRBS from a hatchling revealed that less than 10% of CpGs are methylated, highlighting a non-random distribution in the genome of all tissues, with enrichment in the bodies of a subset of 14,000 genes and absence from transposons. Each DNA methylation pattern encompassed genes with distinct functions and, strikingly, many of these genes showed similar expression levels across tissues. In contrast to the static pattern of DNA methylation, the histone marks H3K27me3, H3K9me3 and H3K4me3 were detected at different levels in diverse cephalopod tissues. This suggests the methylome and histone code cooperate to regulate tissue specific gene expression in a way that may be unique to cephalopods.
scCODE: an R package for personalized differentially expressed gene detection on single-cell RNA-sequencing data
Authors: Zou Jiawei , Wang Miaochen , Zhang Zhen , Liu Zheqi , Zhang Xiaobin , Hua Rong , Chen Ke , Zou Xin , Hao Jie 
Published: November 2021

AbstractDifferential expression (DE) gene detection in single-cell RNA-seq (scRNA-seq) data is a key step to understand the biological question investigated. We find that DE methods together with gene filtering have profound impact on DE gene identification, and different datasets will benefit from personalized DE gene detection strategies. Existing tools don’t take gene filtering into consideration, and couldn’t evaluate DE performance on real datasets without prior knowledge of true results. Based on two new metrics, we propose scCODE (single cell Consensus Optimization of Differentially Expressed gene detection), an R package to automatically optimize DE gene detection for each experimental scRNA-seq dataset.
Mechanistic insights into global suppressors of protein folding defects
Authors: Chattopadhyay Gopinath , Bhowmick Jayantika , Manjunath Kavyashree , Ahmed Shahbaz , Goyal Parveen , Varadarajan Raghavan 
Published: November 2021

AbstractMost amino acid substitutions in a protein either lead to partial loss of function or are near neutral. Several studies have shown the existence of second-site mutations that can rescue defects caused by diverse loss of function mutations. Such global suppressor mutations are key drivers of protein evolution. However, the mechanisms responsible for such suppression remain poorly understood. To address this, we characterized multiple suppressor mutations both in isolation and in combination with inactive mutants. We examined six global suppressors of the bacterial toxin CcdB, the known M182T global suppressor of TEM-1 β-lactamase, the N239Y global suppressor of p53-DBD and three suppressors of the SARS-CoV-2 spike Receptor Binding Domain. The suppressors both alone, and in conjunction with inactive mutants, stabilise the protein both thermodynamically and kinetically in-vitro, predominantly through acceleration of the refolding rate. When coupled to inactive mutants they promote increased in-vivo solubilities as well as regain-of-function phenotypes. In the case of CcdB, where novel suppressors were isolated, we determined the crystal structures of three such suppressors to obtain insight into the specific molecular interactions responsible for the observed effects. While most individual suppressors result in small stability enhancements relative to wildtype, which can be combined to yield significant stability increases, thermodynamic stabilisation is neither necessary nor sufficient for suppressor action.
Probabilistic representations as building blocks for higher-level vision
Authors: Chetverikov Andrey , Kristjánsson Árni 
Published: November 2021

AbstractCurrent theories of perception suggest that the brain represents features of the world as probability distributions, but can such uncertain foundations provide the basis for everyday vision? Perceiving objects and scenes requires knowing not just how features (e.g., colors) are distributed but also where they are and which other features they are combined with. Using a Bayesian computational model, we recover probabilistic representations used by human observers to search for odd stimuli among distractors. Importantly, we found that the brain integrates information between feature dimensions and spatial locations, leading to more precise representations compared to when information integration is not possible. We also uncover representational asymmetries and biases, showing their spatial organization and arguing against simplified “summary statistics” accounts. Our results confirm that probabilistically encoded visual features are bound with other features and to particular locations, proving how probabilistic representations can be a foundation for higher-level vision.
Double mutant of chymotrypsin inhibitor 2 stabilized through increased conformational entropy
Authors: Gavrilov Yulian , Kümmerer Felix , Orioli Simone , Prestel Andreas , Lindorff-Larsen Kresten , Teilum Kaare 
Published: November 2021

ABSTRACTThe conformational heterogeneity of a folded protein can affect both its function but also stability and folding. We recently discovered and characterized a stabilized double mutant (L49I/I57V) of the protein CI2 and showed that state-of-the-art prediction methods could not predict the increased stability relative to the wild-type protein. Here we have examined whether changed native state dynamics, and resulting entropy changes, can explain the stability changes in the double mutant protein, as well as the two single mutant forms. We have combined NMR relaxation measurements of the ps-ns dynamics of amide groups in the backbone and the methyl groups in the side-chains with molecular dynamics simulations to quantify the native state dynamics. The NMR experiments reveal that the mutations have different effects on the conformational flexibility of CI2: A reduction in conformational dynamics (and entropy) of the native state of L49I variant correlates with its decreased stability, while increased dynamics of the I57V and L49I/I57V variants correlates with their increased stability. These findings suggest that explicitly accounting for changes in native state entropy might be needed to improve the predictions of the effect of mutations on protein stability.