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Developing new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through uniform resource locators (URLs) published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed “easy to install,” and 28% of the tools failed to be installed at all because of problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software. [ABSTRACT FROM AUTHOR]

In 2024, all biology is computational biology. Computer-aided analysis continues to spread into new fields, becoming more accessible to researchers trained in the wet lab who are eager to take advantage of growing datasets, falling costs, and novel assays that present new opportunities for discovery. It is currently much easier to find guidance for implementing these techniques than for reporting their use, leaving biologists to guess which details and files are relevant. In this essay, we review existing literature on the topic, summarize common tips, and link to additional resources for training. Following this overview, we then provide a set of recommendations for sharing code, with an eye toward guiding those who are comparatively new to applying open science principles to their computational work. Taken together, we provide a guide for biologists who seek to follow code sharing best practices but are unsure where to start. For those who want to share their code but don't know where to start, this Essay distils dozens of articles on reproducibility and research software, collecting the most important practical details of how to provide computational transparency even if you aren't a trained software developer. [ABSTRACT FROM AUTHOR]

Two recent papers highlight the fascinating comparative genomics of anhydrobiosis, the ability to withstand complete desiccation, in bdelloid rotifers and tardigrades. However, both groups had to openly deal with the significant difficulties of generating and interpreting short-read draft assemblies—especially challenging in microscopic species with high sequence polymorphism. These exemplars demonstrate the need to go beyond single draft-quality reference genomes to high-quality multiple species comparative genomics if we are to fully capture the value of genomics. [ABSTRACT FROM AUTHOR]

Data, including information generated from them by processing and analysis, are an asset with measurable value. The assets that biological research funding produces are the data generated, the information derived from these data, and, ultimately, the discoveries and knowledge these lead to. From the time when Henry Oldenburg published the first scientific journal in 1665 (Proceedings of the Royal Society) to the founding of the United States National Library of Medicine in 1879 to the present, there has been a sustained drive to improve how researchers can record and discover what is known. Researchers’ experimental work builds upon years and (collectively) billions of dollars’ worth of earlier work. Today, researchers are generating data at ever-faster rates because of advances in instrumentation and technology, coupled with decreases in production costs. Unfortunately, the ability of researchers to manage and disseminate their results has not kept pace, so their work cannot achieve its maximal impact. Strides have recently been made, but more awareness is needed of the essential role that biological data resources, including biocuration, play in maintaining and linking this ever-growing flood of data and information. The aim of this paper is to describe the nature of data as an asset, the role biocurators play in increasing its value, and consistent, practical means to measure effectiveness that can guide planning and justify costs in biological research information resources’ development and management. [ABSTRACT FROM AUTHOR]

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science. Do you want to attract computational biologists to your project or to your department? Despite the major contributions of computational biology, those attempting to bridge the interdisciplinary gap often languish in career advancement, publication, and grant review. Here, sixteen computational biologists around the globe present "A field guide to cultivating computational biology," focusing on solutions. [ABSTRACT FROM AUTHOR]

Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regularly updated data present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow leverages tools from software development, including version control and continuous integration, to create a modern data management system that automates the pipeline. [ABSTRACT FROM AUTHOR]

The article focuses on the study of allele frequencies and quantitative genetics. Topics discussed include analysis of data for evaluating the role of evolutionary genetics; analysis of deep sequencing and genome-wide association study on the same; and analysis of genetic variation in heritability estimates.

Biological systems are so complex that we must ask: "What purpose does all this complexity serve?" Lander argues that computational biology may help provide answers. [ABSTRACT FROM AUTHOR]

How a child's brain develops specialization for print is poorly understood. One longstanding account is selective neuronal tuning to regularity of visual-orthographic features, which predicts a monotonically increased neural activation for inputs with higher regularity during development. However, we observed a robust interaction between a stimulus' orthographic regularity (bottom-up input) and children's lexical classification ability (top-down prediction): N1 response, which is the first negative component of the event-related potential (ERP) occurring at posterior electrodes, was stronger to lower-regularity stimuli, but only in children who were less efficient in lexically classifying these stimuli (high prediction error). In contrast, N1 responses were reduced to lower-regularity stimuli in children who showed high efficiency of lexical classification (low prediction error). The modulation of children's lexical classification efficiency on their neural responses to orthographic stimuli supports the predictive coding account of neural processes of reading. [ABSTRACT FROM AUTHOR]

Predictive processing (e.g., predictive coding) is a predominant paradigm in cognitive neuroscience. This Primer considers the various levels of commitment neuroscientists have to the neuronal process theories that accompany the principles of predictive processing. Specifically, it reviews and contextualises a recent PLOS Biology study of alpha oscillations and travelling waves. We will see that alpha oscillations emerge naturally under the computational architectures implied by predictive coding-and may tell us something profound about recurrent message passing in brain hierarchies. Specifically, the bidirectional nature of forward and backward waves speaks to opportunities to understand attention and how it nuances bottom-up and top-down influences. [ABSTRACT FROM AUTHOR]

The number of the distinct tactile percepts exceeds the number of receptor types in the skin, signifying that perception cannot be explained by a one-to-one mapping from a single receptor channel to a corresponding percept. The abundance of touch experiences results from multiplexing (the coexistence of multiple codes within a single channel, increasing the available information content of that channel) and from the mixture of receptor channels by divergence and convergence. When a neuronal representation emerges through the combination of receptor channels, perceptual uncertainty can occur—a perceptual judgment is affected by a stimulus feature that would be, ideally, excluded from the task. Though uncertainty seems at first glance to reflect nonoptimality in sensory processing, it is actually a consequence of efficient coding mechanisms that exploit prior knowledge about objects that are touched. Studies that analyze how perceptual judgments are “fooled” by variations in sensory input can reveal the neuronal mechanisms underlying the tactile experience. [ABSTRACT FROM AUTHOR]

Attending to visual stimuli enhances the gain of those neurons in primate visual cortex that preferentially respond to the matching locations and features (on-target gain). Although this is well suited to enhance the neuronal representation of attended stimuli, it is nonoptimal under difficult discrimination conditions, as in the presence of similar distractors. In such cases, directing attention to neighboring neuronal populations (off-target gain) has been shown to be the most efficient strategy, but although such a strategic deployment of attention has been shown behaviorally, its underlying neural mechanisms are unknown. Here, we investigated how attention affects the population responses of neurons in the middle temporal (MT) visual area of rhesus monkeys to bidirectional movement inside the neurons’ receptive field (RF). The monkeys were trained to focus their attention onto the fixation spot or to detect a direction or speed change in one of the motion directions (the “target”), ignoring the distractor motion. Population activity profiles were determined by systematically varying the patterns’ directions while maintaining a constant angle between them. As expected, the response profiles show a peak for each of the 2 motion directions. Switching spatial attention from the fixation spot into the RF enhanced the peak representing the attended stimulus and suppressed the distractor representation. Importantly, the population data show a direction-dependent attentional modulation that does not peak at the target feature but rather along the slopes of the activity profile representing the target direction. Our results show that attentional gains are strategically deployed to optimize the discriminability of target stimuli, in line with an optimal gain mechanism proposed by Navalpakkam and Itti. [ABSTRACT FROM AUTHOR]

While sequencing ancient DNA (aDNA) from archaeological material is now commonplace, very few attempts to sequence ancient transcriptomes have been made, even from typically stable deposition environments such as permafrost. This is presumably due to assumptions that RNA completely degrades relatively quickly, particularly when dealing with autolytic, nuclease-rich mammalian tissues. However, given the recent successes in sequencing ancient RNA (aRNA) from various sources including plants and animals, we suspect that these assumptions may be incorrect or exaggerated. To challenge the underlying dogma, we generated shotgun RNA data from sources that might normally be dismissed for such study. Here, we present aRNA data generated from two historical wolf skins, and permafrost-preserved liver tissue of a 14,300-year-old Pleistocene canid. Not only is the latter the oldest RNA ever to be sequenced, but it also shows evidence of biologically relevant tissue specificity and close similarity to equivalent data derived from modern-day control tissue. Other hallmarks of RNA sequencing (RNA-seq) data such as exon-exon junction presence and high endogenous ribosomal RNA (rRNA) content confirms our data’s authenticity. By performing independent technical library replicates using two high-throughput sequencing platforms, we show not only that aRNA can survive for extended periods in mammalian tissues but also that it has potential for tissue identification. aRNA also has possible further potential, such as identifying in vivo genome activity and adaptation, when sequenced using this technology. [ABSTRACT FROM AUTHOR]

Speciation genomic studies aim to interpret patterns of genome-wide variation in light of the processes that give rise to new species. However, interpreting the genomic “landscape” of speciation is difficult, because many evolutionary processes can impact levels of variation. Facilitated by the first chromosome-level assembly for the group, we use whole-genome sequencing and simulations to shed light on the processes that have shaped the genomic landscape during a radiation of monkeyflowers. After inferring the phylogenetic relationships among the 9 taxa in this radiation, we show that highly similar diversity (π) and differentiation (FST) landscapes have emerged across the group. Variation in these landscapes was strongly predicted by the local density of functional elements and the recombination rate, suggesting that the landscapes have been shaped by widespread natural selection. Using the varying divergence times between pairs of taxa, we show that the correlations between FST and genome features arose almost immediately after a population split and have become stronger over time. Simulations of genomic landscape evolution suggest that background selection (BGS; i.e., selection against deleterious mutations) alone is too subtle to generate the observed patterns, but scenarios that involve positive selection and genetic incompatibilities are plausible alternative explanations. Finally, tests for introgression among these taxa reveal widespread evidence of heterogeneous selection against gene flow during this radiation. Combined with previous evidence for adaptation in this system, we conclude that the correlation in FST among these taxa informs us about the processes contributing to adaptation and speciation during a rapid radiation. [ABSTRACT FROM AUTHOR]

The developmental pathway of the neural retina (NR) and retinal pigment epithelium (RPE) has been revealed by extensive research in mice. However, the molecular mechanisms underlying the development of the human NR and RPE, as well as the interactions between these two tissues, have not been well defined. Here, we analyzed 2,421 individual cells from human fetal NR and RPE using single-cell RNA sequencing (RNA-seq) technique and revealed the tightly regulated spatiotemporal gene expression network of human retinal cells. We identified major cell classes of human fetal retina and potential crucial transcription factors for each cell class. We dissected the dynamic expression patterns of visual cycle– and ligand-receptor interaction–related genes in the RPE and NR. Moreover, we provided a map of disease-related genes for human fetal retinal cells and highlighted the importance of retinal progenitor cells as potential targets of inherited retinal diseases. Our findings captured the key in vivo features of the development of the human NR and RPE and offered insightful clues for further functional studies. [ABSTRACT FROM AUTHOR]

A morphospecies is defined as a taxonomic species based wholly on morphology, but often morphospecies consist of clusters of cryptic species that can be identified genetically or molecularly. The nature of the evolutionary novelty that accompanies speciation in a morphospecies is an intriguing question. Morphospecies are particularly common among ciliates, a group of unicellular eukaryotes that separates 2 kinds of nuclei—the silenced germline nucleus (micronucleus [MIC]) and the actively expressed somatic nucleus (macronucleus [MAC])—within a common cytoplasm. Because of their very similar morphologies, members of the Tetrahymena genus are considered a morphospecies. We explored the hidden genomic evolution within this genus by performing a comprehensive comparative analysis of the somatic genomes of 10 species and the germline genomes of 2 species of Tetrahymena. These species show high genetic divergence; phylogenomic analysis suggests that the genus originated about 300 million years ago (Mya). Seven universal protein domains are preferentially included among the species-specific (i.e., the youngest) Tetrahymena genes. In particular, leucine-rich repeat (LRR) genes make the largest contribution to the high level of genome divergence of the 10 species. LRR genes can be sorted into 3 different age groups. Parallel evolutionary trajectories have independently occurred among LRR genes in the different Tetrahymena species. Thousands of young LRR genes contain tandem arrays of exactly 90-bp exons. The introns separating these exons show a unique, extreme phase 2 bias, suggesting a clonal origin and successive expansions of 90-bp–exon LRR genes. Identifying LRR gene age groups allowed us to document a Tetrahymena intron length cycle. The youngest 90-bp exon LRR genes in T. thermophila are concentrated in pericentromeric and subtelomeric regions of the 5 micronuclear chromosomes, suggesting that these regions act as genome innovation centers. Copies of a Tetrahymena Long interspersed element (LINE)-like retrotransposon are very frequently found physically adjacent to 90-bp exon/intron repeat units of the youngest LRR genes. We propose that Tetrahymena species have used a massive exon-shuffling mechanism, involving unequal crossing over possibly in concert with retrotransposition, to create the unique 90-bp exon array LRR genes. [ABSTRACT FROM AUTHOR]

Sensory experience elicits complex activity patterns throughout the neocortex. Projections from the neocortex converge onto the medial temporal lobe (MTL), in which distributed neocortical firing patterns are distilled into sparse representations. The precise nature of these neuronal representations is still unknown. Here, we show that population activity patterns in the MTL are governed by high levels of semantic abstraction. We recorded human single-unit activity in the MTL (4,917 units, 25 patients) while subjects viewed 100 images grouped into 10 semantic categories of 10 exemplars each. High levels of semantic abstraction were indicated by representational similarity analyses (RSAs) of patterns elicited by individual stimuli. Moreover, pattern classifiers trained to decode semantic categories generalised successfully to unseen exemplars, and classifiers trained to decode exemplar identity more often confused exemplars of the same versus different categories. Semantic abstraction and generalisation may thus be key to efficiently distill the essence of an experience into sparse representations in the human MTL. Although semantic abstraction is efficient and may facilitate generalisation of knowledge to novel situations, it comes at the cost of a loss of detail and may be central to the generation of false memories. [ABSTRACT FROM AUTHOR]

Centromeres are essential chromosomal regions that mediate kinetochore assembly and spindle attachments during cell division. Despite their functional conservation, centromeres are among the most rapidly evolving genomic regions and can shape karyotype evolution and speciation across taxa. Although significant progress has been made in identifying centromere-associated proteins, the highly repetitive centromeres of metazoans have been refractory to DNA sequencing and assembly, leaving large gaps in our understanding of their functional organization and evolution. Here, we identify the sequence composition and organization of the centromeres of Drosophila melanogaster by combining long-read sequencing, chromatin immunoprecipitation for the centromeric histone CENP-A, and high-resolution chromatin fiber imaging. Contrary to previous models that heralded satellite repeats as the major functional components, we demonstrate that functional centromeres form on islands of complex DNA sequences enriched in retroelements that are flanked by large arrays of satellite repeats. Each centromere displays distinct size and arrangement of its DNA elements but is similar in composition overall. We discover that a specific retroelement, G2/Jockey-3, is the most highly enriched sequence in CENP-A chromatin and is the only element shared among all centromeres. G2/Jockey-3 is also associated with CENP-A in the sister species D. simulans, revealing an unexpected conservation despite the reported turnover of centromeric satellite DNA. Our work reveals the DNA sequence identity of the active centromeres of a premier model organism and implicates retroelements as conserved features of centromeric DNA. [ABSTRACT FROM AUTHOR]

Malaria parasites possess the remarkable ability to maintain chronic infections that fail to elicit a protective immune response, characteristics that have stymied vaccine development and cause people living in endemic regions to remain at risk of malaria despite previous exposure to the disease. These traits stem from the tremendous antigenic diversity displayed by parasites circulating in the field. For Plasmodium falciparum, the most virulent of the human malaria parasites, this diversity is exemplified by the variant gene family called var, which encodes the major surface antigen displayed on infected red blood cells (RBCs). This gene family exhibits virtually limitless diversity when var gene repertoires from different parasite isolates are compared. Previous studies indicated that this remarkable genome plasticity results from extensive ectopic recombination between var genes during mitotic replication; however, the molecular mechanisms that direct this process to antigen-encoding loci while the rest of the genome remains relatively stable were not determined. Using targeted DNA double-strand breaks (DSBs) and long-read whole-genome sequencing, we show that a single break within an antigen-encoding region of the genome can result in a cascade of recombination events leading to the generation of multiple chimeric var genes, a process that can greatly accelerate the generation of diversity within this family. We also found that recombinations did not occur randomly, but rather high-probability, specific recombination products were observed repeatedly. These results provide a molecular basis for previously described structured rearrangements that drive diversification of this highly polymorphic gene family. [ABSTRACT FROM AUTHOR]

Perception likely results from the interplay between sensory information and top-down signals. In this electroencephalography (EEG) study, we utilised the hierarchical frequency tagging (HFT) method to examine how such integration is modulated by expectation and attention. Using intermodulation (IM) components as a measure of nonlinear signal integration, we show in three different experiments that both expectation and attention enhance integration between top-down and bottom-up signals. Based on a multispectral phase coherence (MSPC) measure, we present two direct physiological measures to demonstrate the distinct yet related mechanisms of expectation and attention, which would not have been possible using other amplitude-based measures. Our results link expectation to the modulation of descending signals and to the integration of top-down and bottom-up information at lower levels of the visual hierarchy. Meanwhile, the results link attention to the modulation of ascending signals and to the integration of information at higher levels of the visual hierarchy. These results are consistent with the predictive coding account of perception. [ABSTRACT FROM AUTHOR]

Whole-brain recordings give us a global perspective of the brain in action. In this study, we describe a method using light field microscopy to record near-whole brain calcium and voltage activity at high speed in behaving adult flies. We first obtained global activity maps for various stimuli and behaviors. Notably, we found that brain activity increased on a global scale when the fly walked but not when it groomed. This global increase with walking was particularly strong in dopamine neurons, which showed little activity otherwise. Second, we extracted maps of spatially distinct sources of activity as well as their time series using principal component analysis and independent component analysis. The characteristic shapes in the maps matched the anatomy of subneuropil regions and, in some cases, a specific neuron type. Brain structures that responded to light and odor were consistent with previous reports, confirming the new technique’s validity. We also observed previously uncharacterized behavior-related activity as well as patterns of spontaneous voltage activity. [ABSTRACT FROM AUTHOR]

The global diversity of Bacteria and Archaea, the most ancient and most widespread forms of life on Earth, is a subject of intense controversy. This controversy stems largely from the fact that existing estimates are entirely based on theoretical models or extrapolations from small and biased data sets. Here, in an attempt to census the bulk of Earth's bacterial and archaeal ("prokaryotic") clades and to estimate their overall global richness, we analyzed over 1.7 billion 16S ribosomal RNA amplicon sequences in the V4 hypervariable region obtained from 492 studies worldwide, covering a multitude of environments and using multiple alternative primers. From this data set, we recovered 739,880 prokaryotic operational taxonomic units (OTUs, 16S-V4 gene clusters at 97% similarity), a commonly used measure of microbial richness. Using several statistical approaches, we estimate that there exist globally about 0.8–1.6 million prokaryotic OTUs, of which we recovered somewhere between 47%–96%, representing >99.98% of prokaryotic cells. Consistent with this conclusion, our data set independently "recaptured" 91%–93% of 16S sequences from multiple previous global surveys, including PCR-independent metagenomic surveys. The distribution of relative OTU abundances is consistent with a log-normal model commonly observed in larger organisms; the total number of OTUs predicted by this model is also consistent with our global richness estimates. By combining our estimates with the ratio of full-length versus partial-length (V4) sequence diversity in the SILVA sequence database, we further estimate that there exist about 2.2–4.3 million full-length OTUs worldwide. When restricting our analysis to the Americas, while controlling for the number of studies, we obtain similar richness estimates as for the global data set, suggesting that most OTUs are globally distributed. Qualitatively similar results are also obtained for other 16S similarity thresholds (90%, 95%, and 99%). Our estimates constrain the extent of a poorly quantified rare microbial biosphere and refute recent predictions that there exist trillions of prokaryotic OTUs. [ABSTRACT FROM AUTHOR]

Increasingly complex statistical models are being used for the analysis of biological data. Recent commentary has focused on the ability to compute the same outcome for a given dataset (reproducibility). We argue that a reproducible statistical analysis is not necessarily valid because of unique patterns of nonindependence in every biological dataset. We advocate that analyses should be evaluated with known-truth simulations that capture biological reality, a process we call “analysis validation.” We review the process of validation and suggest criteria that a validation project should meet. We find that different fields of science have historically failed to meet all criteria, and we suggest ways to implement meaningful validation in training and practice. [ABSTRACT FROM AUTHOR]

Understanding how neurons encode and compute information is fundamental to our study of the brain, but opportunities for hands-on experience with neurophysiological techniques on live neurons are scarce in science education. Here, we present Spikeling, an open source in silico implementation of a spiking neuron that costs £25 and mimics a wide range of neuronal behaviours for classroom education and public neuroscience outreach. Spikeling is based on an Arduino microcontroller running the computationally efficient Izhikevich model of a spiking neuron. The microcontroller is connected to input ports that simulate synaptic excitation or inhibition, to dials controlling current injection and noise levels, to a photodiode that makes Spikeling light sensitive, and to a light-emitting diode (LED) and speaker that allows spikes to be seen and heard. Output ports provide access to variables such as membrane potential for recording in experiments or digital signals that can be used to excite other connected Spikelings. These features allow for the intuitive exploration of the function of neurons and networks mimicking electrophysiological experiments. We also report our experience of using Spikeling as a teaching tool for undergraduate and graduate neuroscience education in Nigeria and the United Kingdom. [ABSTRACT FROM AUTHOR]

In this Open Highlight, Senior Editor Lauren Richardson features exciting new Open Access research into how species evolve their characteristic traits. [ABSTRACT FROM AUTHOR]

Biomedical research has been previously reported to primarily focus on a minority of all known genes. Here, we demonstrate that these differences in attention can be explained, to a large extent, exclusively from a small set of identifiable chemical, physical, and biological properties of genes. Together with knowledge about homologous genes from model organisms, these features allow us to accurately predict the number of publications on individual human genes, the year of their first report, the levels of funding awarded by the National Institutes of Health (NIH), and the development of drugs against disease-associated genes. By explicitly identifying the reasons for gene-specific bias and performing a meta-analysis of existing computational and experimental knowledge bases, we describe gene-specific strategies for the identification of important but hitherto ignored genes that can open novel directions for future investigation. [ABSTRACT FROM AUTHOR]

Temporarily holding information in mind is an important part of many cognitive processes, such as reasoning and language. The amount of information that can be actively held “in mind” at any time is greatly limited—research suggests that we can only actively hold three or four pieces of information at once. A central question in cognitive neuroscience is how a system comprised of billions of neurons can actively maintain such a limited amount of information. A new study published in this issue of PLOS Biology by Bahramisharif and colleagues provides significant insights into this question. [ABSTRACT FROM AUTHOR]

A key component of working memory is the ability to remember multiple items simultaneously. To understand how the human brain maintains multiple items in memory, we examined direct brain recordings of neural oscillations from neurosurgical patients as they performed a working memory task. We analyzed the data to identify the neural representations of individual memory items by identifying recording sites with broadband gamma activity that varied according to the identity of the letter a subject viewed. Next, we tested a previously proposed model of working memory, which had hypothesized that the neural representations of individual memory items sequentially occurred at different phases of the theta/alpha cycle. Consistent with this model, the phase of the theta/alpha oscillation when stimulus-related gamma activity occurred during maintenance reflected the order of list presentation. These results suggest that working memory is organized by a cortical phase code coordinated by coupled theta/alpha and gamma oscillations and, more broadly, provide support for the serial representation of items in working memory. [ABSTRACT FROM AUTHOR]

The ability to simultaneously process and maintain multiple pieces of information is limited. Over the past 50 years, observational methods have provided a large amount of insight regarding the neural mechanisms that underpin the mental capacity that we refer to as “working memory.” More than 20 years ago, a neural coding scheme was proposed for working memory. As a result of technological developments, we can now not only observe but can also influence brain rhythms in humans. Building on these novel developments, we have begun to externally control brain oscillations in order to extend the limits of working memory. [ABSTRACT FROM AUTHOR]

Within the human host, the malaria parasite Plasmodium falciparum is exposed to multiple selection pressures. The host environment changes dramatically in severe malaria, but the extent to which the parasite responds to—or is selected by—this environment remains unclear. From previous studies, the parasites that cause severe malaria appear to increase expression of a restricted but poorly defined subset of the PfEMP1 variant, surface antigens. PfEMP1s are major targets of protective immunity. Here, we used RNA sequencing (RNAseq) to analyse gene expression in 44 parasite isolates that caused severe and uncomplicated malaria in Papuan patients. The transcriptomes of 19 parasite isolates associated with severe malaria indicated that these parasites had decreased glycolysis without activation of compensatory pathways; altered chromatin structure and probably transcriptional regulation through decreased histone methylation; reduced surface expression of PfEMP1; and down-regulated expression of multiple chaperone proteins. Our RNAseq also identified novel associations between disease severity and PfEMP1 transcripts, domains, and smaller sequence segments and also confirmed all previously reported associations between expressed PfEMP1 sequences and severe disease. These findings will inform efforts to identify vaccine targets for severe malaria and also indicate how parasites adapt to—or are selected by—the host environment in severe malaria. [ABSTRACT FROM AUTHOR]

Specific members of complex microbiota can influence host phenotypes, depending on both the abiotic environment and the presence of other microorganisms. Therefore, it is challenging to define bacterial combinations that have predictable host phenotypic outputs. We demonstrate that plant–bacterium binary-association assays inform the design of small synthetic communities with predictable phenotypes in the host. Specifically, we constructed synthetic communities that modified phosphate accumulation in the shoot and induced phosphate starvation–responsive genes in a predictable fashion. We found that bacterial colonization of the plant is not a predictor of the plant phenotypes we analyzed. Finally, we demonstrated that characterizing a subset of all possible bacterial synthetic communities is sufficient to predict the outcome of untested bacterial consortia. Our results demonstrate that it is possible to infer causal relationships between microbiota membership and host phenotypes and to use these inferences to rationally design novel communities. [ABSTRACT FROM AUTHOR]

The article covers topics related to neural oscillations. Topics discussed include the importance of entrainment of ongoing neural oscillations as a key mechanism used by the brain to create temporal predictions and support active perception of the sensory cortices, the measures of neural phase coherence or phase concentration, and the use of non-rhythmic information like the passage of time to form temporal predictions.

Blastocystis is the most prevalent eukaryotic microbe colonizing the human gut, infecting approximately 1 billion individuals worldwide. Although Blastocystis has been linked to intestinal disorders, its pathogenicity remains controversial because most carriers are asymptomatic. Here, the genome sequence of Blastocystis subtype (ST) 1 is presented and compared to previously published sequences for ST4 and ST7. Despite a conserved core of genes, there is unexpected diversity between these STs in terms of their genome sizes, guanine-cytosine (GC) content, intron numbers, and gene content. ST1 has 6,544 protein-coding genes, which is several hundred more than reported for ST4 and ST7. The percentage of proteins unique to each ST ranges from 6.2% to 20.5%, greatly exceeding the differences observed within parasite genera. Orthologous proteins also display extreme divergence in amino acid sequence identity between STs (i.e., 59%–61% median identity), on par with observations of the most distantly related species pairs of parasite genera. The STs also display substantial variation in gene family distributions and sizes, especially for protein kinase and protease gene families, which could reflect differences in virulence. It remains to be seen to what extent these inter-ST differences persist at the intra-ST level. A full 26% of genes in ST1 have stop codons that are created on the mRNA level by a novel polyadenylation mechanism found only in Blastocystis. Reconstructions of pathways and organellar systems revealed that ST1 has a relatively complete membrane-trafficking system and a near-complete meiotic toolkit, possibly indicating a sexual cycle. Unlike some intestinal protistan parasites, Blastocystis ST1 has near-complete de novo pyrimidine, purine, and thiamine biosynthesis pathways and is unique amongst studied stramenopiles in being able to metabolize α-glucans rather than β-glucans. It lacks all genes encoding heme-containing cytochrome P450 proteins. Predictions of the mitochondrion-related organelle (MRO) proteome reveal an expanded repertoire of functions, including lipid, cofactor, and vitamin biosynthesis, as well as proteins that may be involved in regulating mitochondrial morphology and MRO/endoplasmic reticulum (ER) interactions. In sharp contrast, genes for peroxisome-associated functions are absent, suggesting Blastocystis STs lack this organelle. Overall, this study provides an important window into the biology of Blastocystis, showcasing significant differences between STs that can guide future experimental investigations into differences in their virulence and clarifying the roles of these organisms in gut health and disease. [ABSTRACT FROM AUTHOR]

The Genomic Observatories Metadatabase (GeOMe, ) is an open access repository for geographic and ecological metadata associated with biosamples and genetic data. Whereas public databases have served as vital repositories for nucleotide sequences, they do not accession all the metadata required for ecological or evolutionary analyses. GeOMe fills this need, providing a user-friendly, web-based interface for both data contributors and data recipients. The interface allows data contributors to create a customized yet standard-compliant spreadsheet that captures the temporal and geospatial context of each biosample. These metadata are then validated and permanently linked to archived genetic data stored in the National Center for Biotechnology Information’s (NCBI’s) Sequence Read Archive (SRA) via unique persistent identifiers. By linking ecologically and evolutionarily relevant metadata with publicly archived sequence data in a structured manner, GeOMe sets a gold standard for data management in biodiversity science. [ABSTRACT FROM AUTHOR]

Tardigrada, a phylum of meiofaunal organisms, have been at the center of discussions of the evolution of Metazoa, the biology of survival in extreme environments, and the role of horizontal gene transfer in animal evolution. Tardigrada are placed as sisters to Arthropoda and Onychophora (velvet worms) in the superphylum Panarthropoda by morphological analyses, but many molecular phylogenies fail to recover this relationship. This tension between molecular and morphological understanding may be very revealing of the mode and patterns of evolution of major groups. Limnoterrestrial tardigrades display extreme cryptobiotic abilities, including anhydrobiosis and cryobiosis, as do bdelloid rotifers, nematodes, and other animals of the water film. These extremophile behaviors challenge understanding of normal, aqueous physiology: how does a multicellular organism avoid lethal cellular collapse in the absence of liquid water? Meiofaunal species have been reported to have elevated levels of horizontal gene transfer (HGT) events, but how important this is in evolution, and particularly in the evolution of extremophile physiology, is unclear. To address these questions, we resequenced and reassembled the genome of H. dujardini, a limnoterrestrial tardigrade that can undergo anhydrobiosis only after extensive pre-exposure to drying conditions, and compared it to the genome of R. varieornatus, a related species with tolerance to rapid desiccation. The 2 species had contrasting gene expression responses to anhydrobiosis, with major transcriptional change in H. dujardini but limited regulation in R. varieornatus. We identified few horizontally transferred genes, but some of these were shown to be involved in entry into anhydrobiosis. Whole-genome molecular phylogenies supported a Tardigrada+Nematoda relationship over Tardigrada+Arthropoda, but rare genomic changes tended to support Tardigrada+Arthropoda. [ABSTRACT FROM AUTHOR]

Here, I argue that computational thinking and techniques are so central to the quest of understanding life that today all biology is computational biology. Computational biology brings order into our understanding of life, it makes biological concepts rigorous and testable, and it provides a reference map that holds together individual insights. The next modern synthesis in biology will be driven by mathematical, statistical, and computational methods being absorbed into mainstream biological training, turning biology into a quantitative science. [ABSTRACT FROM AUTHOR]

Collaboration plays an increasingly important role in promoting research productivity and impact. What remains unclear is whether female and male researchers in science, technology, engineering, and mathematical (STEM) disciplines differ in their collaboration propensity. Here, we report on an empirical analysis of the complete publication records of 3,980 faculty members in six STEM disciplines at select U.S. research universities. We find that female faculty have significantly fewer distinct co-authors over their careers than males, but that this difference can be fully accounted for by females’ lower publication rate and shorter career lengths. Next, we find that female scientists have a lower probability of repeating previous co-authors than males, an intriguing result because prior research shows that teams involving new collaborations produce work with higher impact. Finally, we find evidence for gender segregation in some sub-disciplines in molecular biology, in particular in genomics where we find female faculty to be clearly under-represented. [ABSTRACT FROM AUTHOR]

Prospects have never seemed better for a truly global approach to science to improve human health, with leaders of national initiatives laying out their vision of a worldwide network of related projects. An extensive literature addresses obstacles to global genomic data sharing, yet a series of public polls suggests that the scientific community may be overlooking a significant barrier: potential public resistance to data sharing across national borders. In several large United States surveys, university researchers in other countries were deemed the least acceptable group of data users, and a just-completed US survey found a marked increase in privacy and security concerns related to data access by non-US researchers. Furthermore, diminished support for sharing beyond national borders is not unique to the US, although the limited data from outside the US suggest variation across countries as well as demographic groups. Possible sources of resistance include apprehension about privacy and security protections. Strategies for building public support include making the affirmative case for global data sharing, addressing privacy, security, and other legitimate concerns, and investigating public concerns in greater depth. [ABSTRACT FROM AUTHOR]

This Editorial discusses the creation of two new scope-broadening article types for PLOS Biology — Methods & Resources articles and Short Reports — acknowledging that important advances in biology come in many shapes and sizes. [ABSTRACT FROM AUTHOR]

There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system’s dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems. [ABSTRACT FROM AUTHOR]

The primary mechanism of action of the antibiotic dihydrostreptomycin is binding to and modifying the function of the bacterial ribosome, thus leading to decreased and aberrant translation of proteins; however, the routes by which it enters the bacterial cell are largely unknown. The mechanosensitive channel of large conductance, MscL, is found in the vast majority of bacterial species, where it serves as an emergency release valve rescuing the cell from sudden decreases in external osmolarity. While it is known that MscL expression increases the potency of dihydrostreptomycin, it has remained unclear if this effect is due to a direct interaction. Here, we use a combination of genetic screening, MD simulations, and biochemical and mutational approaches to determine if dihydrostreptomycin directly interacts with MscL. Our data strongly suggest that dihydrostreptomycin binds to a specific site on MscL and modifies its conformation, thus allowing the passage of K+ and glutamate out of, and dihydrostreptomycin into, the cell. [ABSTRACT FROM AUTHOR]

There is no unified place where genomics researchers can search through all available raw genomic data in a way similar to OMIM for genes or Uniprot for proteins. With the recent increase in the amount of genomic data that is being produced and the ever-growing promises of precision medicine, this is becoming more and more of a problem. DNAdigest is a charity working to promote efficient sharing of human genomic data to improve the outcome of genomic research and diagnostics for the benefit of patients. Repositive, a social enterprise spin-out of DNAdigest, is building an online platform that indexes genomic data stored in repositories and thus enables researchers to search for and access a range of human genomic data sources through a single, easy-to-use interface, free of charge. [ABSTRACT FROM AUTHOR]

Stimulus-specific adaptation (SSA) in single neurons of the auditory cortex was suggested to be a potential neural correlate of the mismatch negativity (MMN), a widely studied component of the auditory event-related potentials (ERP) that is elicited by changes in the auditory environment. However, several aspects on this SSA/MMN relation remain unresolved. SSA occurs in the primary auditory cortex (A1), but detailed studies on SSA beyond A1 are lacking. To study the topographic organization of SSA, we mapped the whole rat auditory cortex with multiunit activity recordings, using an oddball paradigm. We demonstrate that SSA occurs outside A1 and differs between primary and nonprimary cortical fields. In particular, SSA is much stronger and develops faster in the nonprimary than in the primary fields, paralleling the organization of subcortical SSA. Importantly, strong SSA is present in the nonprimary auditory cortex within the latency range of the MMN in the rat and correlates with an MMN-like difference wave in the simultaneously recorded local field potentials (LFP). We present new and strong evidence linking SSA at the cellular level to the MMN, a central tool in cognitive and clinical neuroscience. [ABSTRACT FROM AUTHOR]

The ecologically significant shift in developmental strategy from planktotrophic (feeding) to lecithotrophic (nonfeeding) development in the sea urchin genus Heliocidaris is one of the most comprehensively studied life history transitions in any animal. Although the evolution of lecithotrophy involved substantial changes to larval development and morphology, it is not known to what extent changes in gene expression underlie the developmental differences between species, nor do we understand how these changes evolved within the context of the well-defined gene regulatory network (GRN) underlying sea urchin development. To address these questions, we used RNA-seq to measure expression dynamics across development in three species: the lecithotroph Heliocidaris erythrogramma, the closely related planktotroph H. tuberculata, and an outgroup planktotroph Lytechinus variegatus. Using well-established statistical methods, we developed a novel framework for identifying, quantifying, and polarizing evolutionary changes in gene expression profiles across the transcriptome and within the GRN. We found that major changes in gene expression profiles were more numerous during the evolution of lecithotrophy than during the persistence of planktotrophy, and that genes with derived expression profiles in the lecithotroph displayed specific characteristics as a group that are consistent with the dramatically altered developmental program in this species. Compared to the transcriptome, changes in gene expression profiles within the GRN were even more pronounced in the lecithotroph. We found evidence for conservation and likely divergence of particular GRN regulatory interactions in the lecithotroph, as well as significant changes in the expression of genes with known roles in larval skeletogenesis. We further use coexpression analysis to identify genes of unknown function that may contribute to both conserved and derived developmental traits between species. Collectively, our results indicate that distinct evolutionary processes operate on gene expression during periods of life history conservation and periods of life history divergence, and that this contrast is even more pronounced within the GRN than across the transcriptome as a whole. [ABSTRACT FROM AUTHOR]

Horizontal DNA transfer (HDT) is a pervasive mechanism of diversification in many microbial species, but its primary evolutionary role remains controversial. Much recent research has emphasised the adaptive benefit of acquiring novel DNA, but here we argue instead that intragenomic conflict provides a coherent framework for understanding the evolutionary origins of HDT. To test this hypothesis, we developed a mathematical model of a clonally descended bacterial population undergoing HDT through transmission of mobile genetic elements (MGEs) and genetic transformation. Including the known bias of transformation toward the acquisition of shorter alleles into the model suggested it could be an effective means of counteracting the spread of MGEs. Both constitutive and transient competence for transformation were found to provide an effective defence against parasitic MGEs; transient competence could also be effective at permitting the selective spread of MGEs conferring a benefit on their host bacterium. The coordination of transient competence with cell–cell killing, observed in multiple species, was found to result in synergistic blocking of MGE transmission through releasing genomic DNA for homologous recombination while simultaneously reducing horizontal MGE spread by lowering the local cell density. To evaluate the feasibility of the functions suggested by the modelling analysis, we analysed genomic data from longitudinal sampling of individuals carrying Streptococcus pneumoniae. This revealed the frequent within-host coexistence of clonally descended cells that differed in their MGE infection status, a necessary condition for the proposed mechanism to operate. Additionally, we found multiple examples of MGEs inhibiting transformation through integrative disruption of genes encoding the competence machinery across many species, providing evidence of an ongoing “arms race.” Reduced rates of transformation have also been observed in cells infected by MGEs that reduce the concentration of extracellular DNA through secretion of DNases. Simulations predicted that either mechanism of limiting transformation would benefit individual MGEs, but also that this tactic’s effectiveness was limited by competition with other MGEs coinfecting the same cell. A further observed behaviour we hypothesised to reduce elimination by transformation was MGE activation when cells become competent. Our model predicted that this response was effective at counteracting transformation independently of competing MGEs. Therefore, this framework is able to explain both common properties of MGEs, and the seemingly paradoxical bacterial behaviours of transformation and cell–cell killing within clonally related populations, as the consequences of intragenomic conflict between self-replicating chromosomes and parasitic MGEs. The antagonistic nature of the different mechanisms of HDT over short timescales means their contribution to bacterial evolution is likely to be substantially greater than previously appreciated. [ABSTRACT FROM AUTHOR]

: Imagine if we could compute across phenotype data as easily as genomic data; this article calls for efforts to realize this vision and discusses the potential benefits. [ABSTRACT FROM AUTHOR]

: A computational model yields new insights into the bewildering complexity of cortico-striatal plasticity and its rationale for supporting operant learning. [ABSTRACT FROM AUTHOR]

: Experiments using a digital host-parasite model system show that coevolution can drive the emergence of complex traits and more evolvable genomes. Homepage Title: Parasitism Drives the Evolution of Complexity [ABSTRACT FROM AUTHOR]

: Modeling how PRD1, a dsDNA membrane-containing virus, packages its genome using electron cryo-microscopy. [ABSTRACT FROM AUTHOR]

: How neurons pay attention Top-down selective attention mediates feature selection by reducing the noise correlations in neural populations and enhancing the synchronized activity across subpopulations that encode the relevant features of sensory stimuli. [ABSTRACT FROM AUTHOR]