Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 66,973 bioRxiv papers from 294,811 authors.
Most tweeted bioRxiv papers, last 24 hours
416 results found. For more information, click each entry to expand.
6 tweets neuroscience
Miao Jing, Yuexuan Li, Jianzhi Zeng, Pengcheng Huang, Miguel Skirzewski, Wanling Peng, Tongrui Qian, Ke Tan, Runlong Wu, Shichen Zhang, Sunlei Pan, Min Xu, Haohong Li, Lisa M Saksida, Vinia F Prado, Tim Bussey, Marco A.M. Prado, Liangyi Chen, Heping Cheng, Yulong Li
The ability to directly measure acetylcholine (ACh) release is an essential first step towards understanding its physiological function. Here we optimized the GRABACh (GPCR-Activation-Based-ACh) sensor with significantly improved sensitivity and minimal downstream coupling. Using this sensor, we measured in-vivo cholinergic activity in both Drosophila and mice, revealing compartmental ACh signals in fly olfactory center and single-trial ACh dynamics in multiple regions of the mice brain under a variety of different behaviors
6 tweets immunology
Franz Fenninger, Shawna R Stanwood, Chieh-Ju Lu, Cheryl G Pfeifer, Omar Khan, Neil D Romberg, Ramin Herati, E. John Wherry, Kaitlin C O'Boyle, Sarah E. Henrickson, Kelly Maurer, Melanie A Ruffner, Wilfred A Jefferies, Kathleen E Sullivan
Human primary immunodeficiencies are inherited diseases that can provide valuable insight into the immune system. Calcium is a vital secondary messenger in T lymphocytes regulating a vast array of important events including maturation, homeostasis, activation, and apoptosis and can enter the cell through CRAC, TRP, and CaV channels. Here we describe three CaV1.4-deficient siblings presenting with X-linked incomplete congenital stationary night blindness as well as an immune phenotype characterized by several recurrent infections. The subjects uniformly exhibited an expansion of central and effector memory T lymphocytes, and evidence of T lymphocytes exhaustion with corresponding upregulation of inhibitory receptors. Moreover, the sustained elevated levels of activation markers on B lymphocytes suggest that they are in a chronic state of activation. This is the first example where the mutation of any CaV channel causes a primary immunodeficiency in humans and establishes the physiological importance of CaV channels in the human immune system.
6 tweets evolutionary biology
Segmentation of high-resolution tomographic data is often an extremely time-consuming task and until recently, has usually relied upon researchers manually selecting materials of interest slice by slice. With the exponential rise in datasets being acquired, this is clearly not a sustainable workflow. In this paper, we apply the Trainable Weka Segmentation (a freely available plugin for the multiplatform program ImageJ) to typical datasets found in archaeological and evolutionary sciences. We demonstrate that Trainable Weka Segmentation can provide a fast and robust method for segmentation and is as effective as other leading-edge machine learning segmentation techniques.
6 tweets neuroscience
The yellow fever mosquito Aedes aegypti is a prolific vector of arboviral and filarial diseases that largely relies on its sense of smell to find humans. To facilitate in-depth analysis of the neural circuitry underlying Ae. aegypti olfactory-driven behaviors, we generated an updated in vitro atlas for the antennal lobe olfactory brain region of this disease vector using two independent neuronal staining methods. We performed morphological reconstructions with replicate fixed, dissected and stained brain samples from adult male and female Ae. aegypti of the LVPib12 genome reference strain and determined that the antennal lobe in both sexes is comprised of approximately 80 discrete glomeruli. Guided by landmark features in the antennal lobe, we found 63 of these glomeruli are stereotypically located in spatially invariant positions within these in vitro preparations. A posteriorly positioned, mediodorsal glomerulus denoted MD1 was identified as the largest spatially invariant glomerulus in the antennal lobe. Spatial organization of glomeruli in a recently field-derived strain of Ae. aegypti from Puerto Rico was conserved, despite differences in antennal lobe shape relative to the inbred LVPib12 strain. This model in vitro atlas will serve as a useful community guide and resource to improve antennal lobe annotation and anatomically map projection patterns of neurons expressing target genes in this olfactory center. It will also facilitate the development of chemotopic maps of odor representation in the mosquito antennal lobe to decode the molecular and cellular basis of Ae. aegypti attraction to human scent and other chemosensory cues.
6 tweets systems biology
Benoit Lehallier, David Gate, Nicholas Schaum, Tibor Nanasi, Song Eun Lee, Hanadie Yousef, Patricia Moran Losada, Daniela Berdnik, Andreas Keller, Joe Verghese, Sanish Sathyan, Claudio Franceschi, Sofiya Milman, Nir Barzilai, Tony Wyss-Coray
Aging is the predominant risk factor for numerous chronic diseases that limit healthspan. Mechanisms of aging are thus increasingly recognized as therapeutic targets. Blood from young mice reverses aspects of aging and disease across multiple tissues, pointing to the intriguing possibility that age-related molecular changes in blood can provide novel insight into disease biology. We measured 2,925 plasma proteins from 4,331 young adults to nonagenarians and developed a novel bioinformatics approach which uncovered profound non-linear alterations in the human plasma proteome with age. Waves of changes in the proteome in the fourth, seventh, and eighth decades of life reflected distinct biological pathways, and revealed differential associations with the genome and proteome of age-related diseases and phenotypic traits. This new approach to the study of aging led to the identification of unexpected signatures and pathways of aging and disease and offers potential pathways for aging interventions.
6 tweets evolutionary biology
In Angiosperms, perennials typically present much higher levels of inbreeding depression than annuals. The mechanisms leading to this pattern are poorly understood. In fact, despite the potential significance of this pattern for important evolutionary questions, only two hypotheses have been proposed to explain it. Based on the fact that mutations occurring in somatic tissues may be passed onto the offspring in plants, because they do not have a segregated germline, the first hypothesis states that more long-lived species may accumulate more somatic mutations as they grow, thereby generating higher inbreeding depression. The second hypothesis, which is not in contradiction with the first, stems from the observation that inbreeding depression is typically expressed across multiple life stages in Angiosperms. It posits that increased inbreeding depression in more long-lived species could also be explained by the fact that mutations, regardless of whether they are produced during mitosis or meiosis, may differ in the way they affect fitness in annual and perennial populations, through the life stages at which they are expressed. In this study, we aim to investigate the second hypothesis, setting aside somatic mutations accumulation. We combine a physiological growth model and multilocus population genetics approaches in order to describe a full genotype-to-phenotype-to-fitness map, where the phenotype relates to fitness through biological assumptions, so that the fitness landscape emerges from biological assumptions instead of being assumed a priori. We study the behaviour of different types of mutations affecting growth or survival, and explore their consequences in terms of inbreeding depression and mutation load. Then, we discuss the role deleterious mutations maintained at mutation-selection balance may play in the coevolution between growth and survival strategies.
5 tweets epidemiology
Introduction: Despite the early development of Google Flu Trends in 2009, digital epidemiology methods have not been adopted widely, with most research focusing on the USA. In this article we demonstrate the prediction of real-time trends in influenza-like illness (ILI) in the Netherlands using search engine query data. Methods: We used flu-related search query data from Google Trends in combination with traditional surveillance data from 40 general sentinel practices to build our predictive models. We introduced an artificial 4-week delay in the use of GP data in the models, in order to test the predictive performance of the search engine data. Simulating the weekly use of a prediction model across the 2017/2018 flu season we used lasso regression to fit 52 prediction models (one for each week) for weekly ILI incidence. We used rolling forecast cross-validation for lambda optimization in each model, minimizing the maximum absolute error. Results: The models accurately predicted the number of ILI cases during the 2017/18 ILI epidemic in real time with a mean absolute error of 1.40 (per 10,000 population) and a maximum absolute error of 6.36. The model would also have identified the onset, peak, and end of the epidemic with reasonable accuracy. The number of predictors that were retained in the prediction models was small, ranging from 3 to 5, with a single keyword (Griep = Flu) having by far the most weight in all models. Discussion: This study demonstrates the feasibility of accurate real-time ILI incidence predictions in the Netherlands using internet search query data. Digital ILI monitoring strategies may be useful in countries with poor surveillance systems, or for monitoring emergent diseases, including influenza pandemics. We hope that this transparent and accessible case study inspires and supports further developments in field of digital epidemiology in Europe and beyond.
5 tweets evolutionary biology
The deleterious effects of inbreeding have been of extreme importance to evolutionary biology, but it has been difficult to characterize the complex interactions between genetic constraints and selection that lead to fitness loss and recovery after inbreeding. Viruses, bacteria, and the selfing nematode Caenorhabditis elegans have been shown to be capable of rapid recovery from the fixation of novel deleterious mutation, however the potential for fitness recovery from fixation of segregating variation under inbreeding in outcrossing organisms is poorly understood. C. remanei is an outcrossing relative of C. elegans with high polymorphic variation and extreme inbreeding depression. Here we sought to characterize changes C. remanei in patterns of genomic diversity after ~30 generations of inbreeding via brother-sister mating followed by several hundred generations of recovery at large population size. As expected, inbreeding led to a large decline in reproductive fitness, but unlike results from mutation accumulation experiments, recovery from inbreeding at large populations sizes generated only very moderate recovery in fitness after 300 generations. At the genomic level, we found that while 66% of ancestral segregating SNPs were fixed in the inbred population, this was far fewer than expected under neutral processes. Under recovery, 36 SNPs across 30 genes involved in alimentary, muscular, nervous and reproductive systems changed reproducibly across all replicates, indicating that strong selection for fitness recovery does exist but is likely mutationally limited due to the large number of potential targets. Our results indicate that recovery from inbreeding depression via new compensatory mutations is likely to be constrained by the large number of segregating deleterious variants present in natural populations, limiting the capacity for rapid evolutionary rescue of small populations.
5 tweets neuroscience
Combining information from multiple sources is a fundamental operation performed by networks of neurons in the brain, whose general principles are still largely unknown. Experimental evidence suggests that combination of inputs in cortex relies on nonlinear summation. Such nonlinearities are thought to be fundamental to perform complex computations. However, these non-linearities contradict the balanced- state model, one of the most popular models of cortical dynamics, which predicts networks have a linear response. This linearity is obtained in the limit of very large recurrent coupling strength. We investigate the stationary response of networks of spiking neurons as a function of coupling strength. We show that, while a linear transfer function emerges at strong coupling, nonlinearities are prominent at finite coupling, both at response onset and close to saturation. We derive a general framework to classify nonlinear responses in these networks and discuss which of them can be captured by rate models. This framework could help to understand the observed diversity of non-linearities observed in cortical networks.
5 tweets genetics
Marie-Christine Birling, Atsushi Yoshiki, David J. Adams, Shinya Ayabe, Arthur L. Beaudet, Joanna Bottomley, Allan Bradley, Steve D.M Brown, Antje B&uumlrger, Wendy Bushell, Francesco Chiani, Hsian-Jean Genie Chin, Skevoulla Christou, Gemma F Codner, Francesco J DeMayo, Mary Dickinson, Brendan Doe, Leah Rae Donahue, Martin D Fray, Alessia Gambadoro, Xiang Gao, Marina Gertsenstein, Alba Gomez-Segura, Leslie O. Goodwin, Jason D. Heaney, Yann H&eacuterault, Martin Hrabe de Angelis, Si-Tse Jiang, Monica J. Justice, Petr Kasparek, Ruairidh E King, Ralf K&uumlhn, Ho Lee, Young Jae Lee, Zhiwei Liu, K C Kent Lloyd, Isabel Lorenzo, Ann-Marie Mallon, Colin McKerlie, Terrence F Meehan, Stuart Newman, Lauryl M.J. Nutter, Goo Taeg Oh, Guillaume Pavlovic, Ramiro Ramirez-Solis, Barry Rosen, Edward J Ryder, Luis A Santos, Joel Schick, John R. Seavitt, Radislav Sedlacek, Claudia Seisenberger, Je Kyung Seong, William C. Skarnes, Tania Sorg, Karen P Steel, Masaru Tamura, Glauco P Tocchini-Valentini, Chi-Kuang Leo Wang, Hannah Wardle-Jones, Marie Wattenhofer-Donz&eacute, Sara Wells, Brandon J Willis, Joshua A Wood, Wolfgang Wurst, Ying Xu, IMPC Consortium, Lydia Teboul, Stephen A. Murray
The International Mouse Phenotyping Consortium reports the generation of new mouse mutant strains for over 5,000 genes from targeted embryonic stem cells on the C57BL/6N genetic background. This includes 2,850 null alleles for which no equivalent mutant mouse line exists, 2,987 novel conditional-ready alleles, and 4,433 novel reporter alleles. This nearly triples the number of genes with reporter alleles and almost doubles the number of conditional alleles available to the scientific community. When combined with more than 30 years of community effort, the total mutant allele mouse resource covers more than half of the genome. The extensively validated collection is archived and distributed through public repositories, facilitating availability to the worldwide biomedical research community, and expanding our understanding of gene function and human disease.
5 tweets biophysics
Alice L B Pyne, Agnes Noy, Kavit Main, Victor Velasco-Berrelleza, Michael M. Piperakis, Lesley A. Mitchenhall, Fiorella M. Cugliandolo, Joseph G. Beton, Clare E M Stevenson, Bart W Hoogenboom, Andrew D. Bates, Anthony Maxwell, Sarah A. Harris
In the cell, DNA is arranged into highly organised and topologically constrained (supercoiled) structures. It remains unclear how this supercoiling affects the double-helix structure of DNA, largely because of limitations in spatial resolution of the available biophysical tools. Here, we overcome these limitations by a combination of atomic force microscopy (AFM) and atomistic molecular dynamics (MD) simulations, to resolve structures of negatively-supercoiled DNA minicircles at base-pair resolution. We observe that negative superhelical stress induces local variation in the canonical B-form DNA structure by introducing kinks and defects that affect global minicircle structure and flexibility. We probe how these local and global conformational changes affect DNA interactions through the binding of triplex-forming oligonucleotides to DNA minicircles. We show that the energetics of triplex formation is governed by a delicate balance between electrostatics and bonding interactions. Our results provide mechanistic insight into how DNA supercoiling can affect molecular recognition of diverse conformational substrates.
5 tweets evolutionary biology
Understanding the genomic processes underlying local adaptation is a central aim of modern evolutionary biology. This task requires identifying footprints of local selection but also estimating spatio-temporal variation of populations demography and variation in recombination rate and diversity along the genome. Here, we investigated these parameters in blue tit populations inhabiting neighbouring deciduous and evergreen forests and populations in an insular versus a continental context. Close populations from deciduous and evergreen habitats were weakly genetically differentiated (FST = 0.004 on average), nevertheless with a significant effect of habitat type on the overall genetic structure. This low differentiation was consistent with the large effective population sizes (from 43,000 to 463,000) and the strong and long-lasting gene flow inferred by demographic modeling. In turn, insular and continental populations were moderately differentiated (FST = 0.08 on average), which was consistent with the inference of moderate ancestral migrations followed by isolation since the end of the last glaciation. Weak and non-parallel footprints of divergent selection among deciduous and evergreen populations were consistent with their demography and the probable polygenic nature of local adaptation in these habitats. This contrasted with stronger outlier regions, more often in regions of low recombination, found between insular and continental populations. Lastly, we identified a genomic inversion on the continent, spanning 2.8Mb. These results provide insights into the demographic history and genetic architecture of local adaptation in blue tit populations at multiple geographic scales.
5 tweets bioinformatics
Correctly predicting features of protein structure and function from amino acid sequence alone remains a supreme challenge for computational biology. For almost three decades, state-of-the-art approaches combined machine learning and evolutionary information from multiple sequence alignments. Exponentially growing sequence databases make it infeasible to gather evolutionary information for entire microbiomes or metaproteomics. On top, for many important proteins (e.g. dark proteome and intrinsically disordered proteins) evolutionary information remains limited. Here, we introduced a novel approach combining recent advances of Language Models (LMs) with multi-task learning to successfully predict aspects of protein structure (secondary structure) and function (cellular component or subcellular localization) without using any evolutionary information from alignments. Our approach fused self-supervised pre-training LMs on an unlabeled big dataset (UniRef50, corresponding to 9.6 billion words) with supervised training on labelled high-quality data in one single end-to-end network. We demonstrated the effectiveness of the novel concept through the successful per-residue prediction of protein secondary structure (Q3=85%, Q8=72%) and through per-protein predictions of localization (Q10=69%) and the distinction between integral membrane and water-soluble proteins (Q2=89%). On top, multi-task predictions are 300-3000 times faster (where HHblits needs 30-300 seconds on average, our method needed 0.045 seconds). These new results push the boundaries of predictability towards grayer and darker areas of the protein space, allowing to make reliable predictions for proteins which were not accessible by previous methods. On top, our method remains scalable as it removes the necessity to search sequence databases for evolutionary related proteins.
5 tweets neuroscience
Human social nature has shaped visual perception. A signature of the relationship between vision and sociality is a particular visual sensitivity to social entities such as faces and bodies. We asked whether human vision also exhibits a special sensitivity to spatial relations that reliably correlate with social relations. In general, interacting people are more often situated face-to-face than back-to-back. Using functional MRI and behavioral measures in female and male human participants, we show that visual sensitivity to social stimuli extends to images including two bodies facing toward (vs. away from) each other. In particular, the inferior lateral occipital cortex, which is involved in visual-object perception, is organized such that the inferior portion encodes the number of bodies (one vs. two) and the superior portion is selectively sensitive to the spatial relation between bodies (facing vs. non-facing). Moreover, functionally localized, body-selective visual cortex responded to facing bodies more strongly than identical, but non-facing, bodies. In this area, multivariate pattern analysis revealed an accurate representation of body dyads with sharpening of the representation of single-body postures in facing dyads, which demonstrates an effect of visual context on the perceptual analysis of a body. Finally, the cost of body inversion (upside-down rotation) on body recognition, a behavioral signature of a specialized mechanism for body perception, was larger for facing vs. non-facing dyads. Thus, spatial relations between multiple bodies are encoded in regions for body perception and affect the way in which bodies are processed. Public Significance Statement Human social nature has shaped visual perception. Here, we show that human vision is not only attuned to socially relevant entities, such as bodies, but also to socially relevant spatial relations between those entities. Body-selective regions of visual cortex respond more strongly to multiple bodies that appear to be interacting (i.e., face-to-face), relative to unrelated bodies, and more accurately represent single body postures in interacting scenarios. Moreover, recognition of facing bodies is particularly susceptible to perturbation by upside-down rotation, indicative of a particular visual sensitivity to the canonical appearance of facing bodies. This encoding of relations between multiple bodies in areas for body-shape recognition suggests that the visual context in which a body is encountered deeply affects its perceptual analysis.
5 tweets evolutionary biology
We develop an analytical framework for predicting the fitness of hybrid genotypes, based on Fisher's geometric model. We first show that all of the model parameters have a simple geometrical and biological interpretation. Hybrid fitness decomposes into intrinsic effects of hybridity and heterozygosity, and extrinsic measures of the (local) adaptedness of the parental lines; and all of these correspond to distances in a phenotypic space. We also show how these quantities change over the course of divergence, with convergence to a characteristic pattern of intrinsic isolation. Using individual-based simulations, we then show that the predictions apply to a wide range of population genetic regimes, and divergence conditions, including allopatry and parapatry, local adaptation and drift. We next connect our results to the quantitative genetics of line crosses in variable or patchy environments. This relates the geometrical distances to quantities that can be estimated from cross data, and provides a simple interpretation of the "composite effects" in the quantitative genetics partition. Finally, we develop extensions to the model, involving selectively-induced disequilibria, and variable phenotypic dominance. The geometry of fitness landscapes provides a unifying framework for understanding speciation, and wider patterns of hybrid fitness.
5 tweets cancer biology
Cancer cell sensitivity or resistance is almost universally quantified through a direct or surrogate measure of cell number. However, compound responses can occur through many distinct phenotypic outcomes including changes in cell growth, apoptosis, and non-apoptotic cell death. These outcomes have distinct effects on the tumor microenvironment, immune responses, and resistance mechanisms. Here, we show that quantifying cell viability alone is insufficient to distinguish between these compound responses. Using an alternative assay and drug response analysis amenable to high-throughput measurement, we find that compounds with identical viability outcomes can have very different effects on cell growth and death. Moreover, compound pairs with additive cell growth and death effects can appear synergistic when only assessed by viability. Overall, these results demonstrate an approach to incorporating measurements of cell death when characterizing a pharmacologic response.
5 tweets evolutionary biology
Emily Sarah Bellis, Elizabeth A Kelly, Claire M Lorts, Huirong Gao, Victoria L Deleo, Germinal Rouhan, Andrew Budden, Govinal B Bhaskara, Zhenbin Hu, Robert Muscarella, Michael P Timko, Baloua Nebie, Steven M Runo, N Doane Chilcoat, Thomas E. Juenger, Geoff Morris, Claude W. dePamphilis, Jesse Lasky
Host-parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica -prone regions and their absence elsewhere implicate potential tradeoffs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and belowground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with tradeoffs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR-Cas9 edited sorghum further indicate the benefit of LGS1 -mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.
5 tweets immunology
We present a flexible, open source R package designed to obtain additional biological and epidemiological insights from commonly available serological datasets. Analysis of serological responses against pathogens with multiple strains such as influenza pose a specific statistical challenge because observed antibody responses measured in serological assays depend both on unobserved prior infections and the resulting cross-reactive antibody dynamics that these infections generate. We provide a general modelling framework to jointly infer these two typically confounded biological processes using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody dynamics that generates expected antibody titres over time. This makes it possible to use observations of antibodies in serological assays to infer an individual's infection history as well as the parameters of the antibody process model. Our aim is to provide a flexible inference package that can be applied to a range of datasets studying different viruses over different timescales. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and cross-reaction, and well as latent epidemiological processes such as attack rates and age-stratified infection risk.
5 tweets microbiology
Many naturally-occurring bacteria lead a lifestyle of metabolic dependency, i.e., they depend on others for crucial resources. We do not understand what factors drive bacteria towards this lifestyle, and how. Here, we systematically show that horizontal gene transfer (HGT) plays a crucial role in the evolution of dependencies in bacteria. Across 835 bacterial species, we map gene gain-loss dynamics on a deep evolutionary tree, and assess the impact of HGT and gene loss on bacterial metabolic networks. Our analyses suggest that genes acquired by HGT can affect which genes are later lost. Dependency evolution is contingent on earlier HGT because of two reasons. First, we find that HGT typically adds new catabolic routes to bacterial metabolic networks. This increases the chance of new metabolic interactions between bacteria, which is a prerequisite for dependency evolution. Second, we show that gaining new routes can promote the loss of specific ancestral routes (a mechanism we call “coupled gains and losses”, CGLs). Phylogenetic patterns indicate that both types of dependencies — those mediated by CGLs and those purely by gene loss — are equally likely. Our results highlight HGT as an important driver of metabolic dependency evolution in bacteria.
5 tweets genomics
Jun Takayama, Shu Tadaka, Kenji Yano, Fumiki Katsuoka, Chinatsu Gocho, Takamitsu Funayama, Satoshi Makino, Yasunobu Okamura, Atsuo Kikuchi, Junko Kawashima, Akihito Otsuki, Jun Yasuda, Shigeo Kure, Kengo Kinoshita, Masayuki Yamamoto, Gen Tamiya
The complete sequence of the human genome is used as a reference for next-generation sequencing analyses. However, some ethnic ancestries are under-represented in the international human reference genome (e.g., GRCh37), especially Asian populations, due to a strong bias toward European and African ancestries in a single mosaic haploid genome consisting chiefly of a single donor. Here, we performed de novo assembly of the genomes from three Japanese male individuals using >100x PacBio long reads and Bionano optical maps per sample. We integrated the genomes using the major allele for consensus, and anchored the scaffolds using sequence-tagged site markers from conventional genetic and radiation hybrid maps to reconstruct each chromosome sequence. The resulting genome sequence, designated JG1, is highly contiguous, accurate, and carries the major allele in the majority of single nucleotide variant sites for a Japanese population. We adopted JG1 as the reference for confirmatory exome re-analyses of seven Japanese families with rare diseases and found that re-analysis using JG1 reduced false-positive variant calls versus GRCh37 while retaining disease-causing variants. These results suggest that integrating multiple genome assemblies from a single ethnic population can aid next-generation sequencing analyses of individuals originated from the population.
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