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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Drought adaptation in nature by extensive genetic loss-of-function

Visions of a second green revolution empowered by emerging technologies have called for interdisciplinary syntheses to scale up the discovery of functionally definitive gene variants responsible for climate adaptation in plants. We integrated novel approaches using whole genome sequences and satellite remote sensing to identify natural knockout alleles associated with drought histories in wild Arabidopsis thaliana. Genes identified exhibit signatures of parallel molecular evolution, selection for loss-of-function alleles, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses 7 times more often than expected by chance. Artificial knockout lines then confirmed predicted phenotypes experimentally. These findings further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature and inspire new opportunities for engineering climate resilience in crops.\n\nOne sentence summaryWhole genome sequences and satellite-detected droughts point to gene knockouts as valuable genetic fuel for climate adaptation.

evolutionary biology↗

bioRxiv2018

Local adaptation under gene flow: Recombination, conditional neutrality and genetic trade-offs shape genomic patterns in Arabidopsis lyrata

Short-scale local adaptation is a complex process involving selection, migration and drift. The expected effects on the genome are well grounded in theory, but examining these on an empirical level has proven difficult, as it requires information about local selection, demographic history and recombination rate variation. Here, we use locally adapted and phenotypically differentiated Arabidopsis lyrata populations from two altitudinal gradients in Norway to test these expectations at the whole-genome level. Demography modelling indicates that populations within the gradients diverged less than 2000 years ago and that the sites are connected by gene flow. The gene flow estimates are, however, highly asymmetric with migration from high to low altitudes being several times more frequent than vice versa. To detect signatures of selection for local adaptation, we estimate patterns of lineage specific differentiation among these populations. Theory predicts that gene flow leads to concentration of adaptive loci in areas of low recombination; a pattern we observe in both lowland-alpine comparisons. Although most selected loci display patterns of conditional neutrality, we found indications of genetic trade-offs, with one locus particularly showing high divergence and signs of selection in both populations. Our results further suggest that resistance to solar radiation is an important adaptation to alpine environments, while vegetative growth and bacterial defense are indicated as selected traits in the lowland habitats. These results provide insights into genetic architectures and evolutionary processes driving local adaptation under gene flow. We also contribute to understanding of traits and biological processes underlying alpine adaptation in northern latitudes.

evolutionary biology↗

bioRxiv2018

Distinct timescales of RNA regulators enable the construction of a genetic pulse generator

To build complex genetic networks with predictable behaviours, synthetic biologists use libraries of modular parts that can be characterized in isolation and assembled together to create programmable higher-order functions. Characterization experiments and computational models for gene regulatory parts operating in isolation are routinely employed to predict the dynamics of interconnected parts and guide the construction of new synthetic devices. Here, we individually characterize two modes of RNA-based transcriptional regulation, using small transcription activating RNAs (STARs) and CRISPR interference (CRISPRi), and show how their distinct regulatory timescales can be used to engineer a composed feedforward loop that creates a pulse of gene expression. We use a cell-free transcription-translation system (TXTL) to rapidly characterize the system, and we apply Bayesian inference to extract kinetic parameters for an ODE-based mechanistic model. We then demonstrate in simulation and verify with TXTL experiments that the simultaneous regulation of a single gene target with STARs and CRISPRi leads to a pulse of gene expression. Our results suggest the modularity of the two regulators in an integrated genetic circuit, and we anticipate that construction and modeling frameworks that can leverage this modularity will become increasingly important as synthetic circuits increase in complexity.

synthetic biology↗

bioRxiv2018

The genetic basis of diurnal preference in Drosophila melanogaster

Most animals restrict their activity to a specific part of the day, being diurnal, nocturnal or crepuscular. The genetic basis underlying diurnal preference is largely unknown. Under laboratory conditions, Drosophila melanogaster is crepuscular, showing a bi-modal activity profile. However, a survey of strains derived from wild populations indicated that high variability among individuals exists, with diurnal and nocturnal flies being observed. Using a highly diverse population, we have carried out an artificial selection experiment, selecting flies with extreme diurnal or nocturnal preference. After 10 generations, we obtained highly diurnal and nocturnal strains. We used whole-genome expression analysis to identify differentially expressed genes in diurnal, nocturnal and crepuscular (control) flies. Other than one circadian clock gene (pdp1), most differentially expressed genes were associated with either clock output (pdf, to) or input (Rh3, Rh2, msn). This finding was congruent with behavioural experiments indicating that both light masking and the circadian pacemaker are involved in driving nocturnality. The diurnal and nocturnal selection strains provide us with a unique opportunity to understand the genetic architecture of diurnal preference.

evolutionary biology↗

bioRxiv2018

A genetic, genomic, and computational resource for exploring neural circuit function

The anatomy of many neural circuits is being characterized with increasing resolution, but their molecular properties remain mostly unknown. Here, we characterize gene expression patterns in distinct neural cell types of the Drosophila visual system using genetic lines to access individual cell types, the TAPIN-seq method to measure their transcriptomes, and a probabilistic method to interpret these measurements. We used these tools to build a resource of high-resolution transcriptomes for 100 driver lines covering 67 cell types, available at http://www.opticlobe.com. Combining these transcriptomes with recently reported connectomes helps characterize how information is transmitted and processed across a range of scales, from individual synapses to circuit pathways. We describe examples that include identifying neurotransmitters, including cases of co-release, generating functional hypotheses based on receptor expression, as well as identifying strong commonalities between different cell types.\n\nHighlightsO_LITranscriptomes reveal transmitters and receptors expressed in Drosophila visual neurons\nC_LIO_LITandem affinity purification of intact nuclei (TAPIN) enables neuronal genomics\nC_LIO_LITAPIN-seq and genetic drivers establish transcriptomes of 67 Drosophila cell types\nC_LIO_LIProbabilistic modeling simplifies interpretation of large transcriptome catalogs\nC_LI

neuroscience↗

bioRxiv2018

A genetically encoded single-wavelength sensor for imaging cytosolic and cell surface ATP

Adenosine 5 triphosphate (ATP) is a universal intracellular energy source1 and an evolutionarily ancient2 extracellular signal3-5. Here, we report the generation and characterization of single-wavelength genetically encoded fluorescent sensors (iATPSnFRs) for imaging extracellular and cytosolic ATP from insertion of circularly permuted superfolder GFP into the epsilon subunit of F0F1-ATPase from Bacillus PS3. On the cell surface and within the cytosol, iATPSnFR1.0 responded to relevant ATP concentrations (30 M to 3 mM) with fast increases in fluorescence. iATPSnFRs can be genetically targeted to specific cell types and sub-cellular compartments, imaged with standard light microscopes, do not respond to other nucleotides and nucleosides, and when fused with a red fluorescent protein function as ratiometric indicators. iATPSnFRs represent promising new reagents for imaging ATP dynamics.

physiology↗

bioRxiv2018

Measuring Illumina Size Bias Using REcount: A Novel Method for Highly Accurate Quantification of Engineered Genetic Constructs

Quantification of DNA sequence tags associated with engineered genetic constructs underlies many genomics measurements. Typically, such measurements are done using PCR to enrich sequence tags and add adapters, followed by next-generation sequencing (NGS). However, PCR amplification can introduce significant quantitative error into these measurements. Here we describe REcount, a novel PCR-free direct counting method for NGS-based quantification of engineered genetic constructs. By comparing measurements of defined plasmid pools to droplet digital PCR data, we demonstrate that this method is highly accurate and reproducible. We further demonstrate that the REcount approach is amenable to multiplexing through the use of orthogonal restriction enzymes. Finally, we use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencing platforms.

genomics↗

bioRxiv2018

A quantitative genetics model for the dynamics of phenotypic (co)variances under limited dispersal, with an application to the coevolution of socially synergistic traits

Darwinian evolution consists of the gradual transformation of heritable quantitative traits due to natural selection and the input of random variation by mutation. Here, we use a quantitative genetics approach to investigate the coevolution of multiple traits under selection, mutation, and limited dispersal. We track the dynamics of trait means and variance-covariances between traits that experience frequency-dependent selection. Assuming a multivariate-normal trait distribution, we recover classical dynamics of quantitative genetics, as well as stability and evolutionary branching conditions of invasion analyses, except that due to limited dispersal, selection depends on indirect fitness effects and relatedness. In particular, correlational selection that associates different traits within-individuals depends on the fitness effects of such associations between-individuals. These kin selection effects can be as relevant as pleiotropy for correlation between traits. We illustrate this with an example of the coevolution of two social traits whose association within-individual is costly but synergistically beneficial between-individuals. As dispersal becomes limited and relatedness increases, associations between-traits between-individuals become increasingly targeted by correlational selection. Consequently, the trait distribution goes from being bimodal with a negative correlation under panmixia to unimodal with a positive correlation under limited dispersal. More broadly, our approach can help understand the evolution of intra-specific variation.

evolutionary biology↗

bioRxiv2018

A pipeline for rapidly generating genetically engineered mouse models of pancreatic cancer using in vivo CRISPR-Cas9 mediated somatic recombination

Genetically engineered mouse models (GEMMs) that recapitulate the major genetic drivers in pancreatic ductal adenocarcinoma (PDAC) have provided unprecedented insights into the pathogenesis of this lethal neoplasm. Nonetheless, generating an autochthonous model is an expensive, time consuming and labor intensive process, particularly when tissue specific expression or deletion of compound alleles are involved. In addition, many of the current PDAC GEMMs cause embryonic, pancreas-wide activation or loss of driver alleles, neither of which reflects the cognate human disease scenario. The advent of CRISPR/Cas9 based gene editing can potentially circumvent many of the aforementioned shortcomings of conventional breeding schema, but ensuring the efficiency of gene editing in vivo remains a challenge. Here we have developed a pipeline for generating PDAC GEMMs of complex genotypes with high efficiency using a single \"workhorse\" mouse strain expressing Cas9 in the adult pancreas under a p48 promoter. Using adeno-associated virus (AAV) mediated delivery of multiplexed guide RNAs (sgRNAs) to the adult murine pancreas of p48-Cre; LSL-Cas9 mice, we confirm our ability to express an oncogenic Kras G12D allele through homology-directed repair (HDR), in conjunction with CRISPR-induced disruption of cooperating alleles (Trp53, Lkb1 and Arid1A). The resulting GEMMs demonstrate a spectrum of precursor lesions (pancreatic intraepithelial neoplasia [PanIN] or Intraductal papillary mucinous neoplasm [IPMN] with eventual progression to PDAC. Next generation sequencing of the resulting murine PDAC confirms HDR of oncogenic KrasG12D allele at the endogenous locus, and insertion deletion (\"indel\") and frameshift mutations of targeted tumor suppressor alleles. By using a single \"workhorse\" mouse strain and optimal AAV serotype for in vivo gene editing with combination of driver alleles, we have created a facile autochthonous platform for interrogation of the PDAC genome.

cancer biology↗

bioRxiv2018

Age of onset in genetic prion disease and the design of preventive clinical trials

Regulatory agencies worldwide have adopted programs to facilitate drug development for diseases where the traditional approach of a randomized trial with a clinical endpoint is expected to be prohibitively lengthy or difficult. Here we provide quantitative evidence that this criterion is met for the prevention of genetic prion disease. We assemble age of onset or death data from N=1,094 individuals with high penetrance mutations in the prion protein gene (PRNP), generate survival and hazard curves, and estimate statistical power for clinical trials. We show that, due to dramatic and unexplained variability in age of onset, randomized preventive trials would require hundreds or thousands of at-risk individuals in order to be statistically powered for an endpoint of clinical onset, posing prohibitive cost and delay and likely exceeding the number of individuals available for such trials. Instead, the characterization of biomarkers suitable to serve as surrogate endpoints will be essential for the prevention of genetic prion disease. Biomarker-based trials may require post-marketing studies to confirm clinical benefit. Parameters such as longer trial duration, increased enrollment, and the use of historical controls in a post-marketing study could provide opportunities for subsequent determination of clinical benefit.

neuroscience↗

bioRxiv2018

Inferring the molecular mechanisms of noncoding Alzheimer’s disease-associated genetic variants

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSWe set out to characterize the causal variants, regulatory mechanisms, tissue contexts, and target genes underlying noncoding late-onset Alzheimers Disease (LOAD)-associated genetic signals.\n\nMETHODSWe applied our INFERNO method to the IGAP genome-wide association study (GWAS) data, annotating all potentially causal variants with tissue-specific regulatory activity. Bayesian co-localization analysis of GWAS summary statistics and eQTL data was performed to identify tissue-specific target genes.\n\nRESULTSINFERNO identified enhancer dysregulation in all 19 tag regions analyzed, significant enrichments of enhancer overlaps in the immune-related blood category, and co-localized eQTL signals overlapping enhancers from the matching tissue class in ten regions (ABCA7, BIN1, CASS4, CD2AP, CD33, CELF1, CLU, EPHA1, FERMT2, ZCWPW1). We validated the allele-specific effects of several variants on enhancer function using luciferase expression assays.\n\nDISCUSSIONIntegrating functional genomics with GWAS signals yielded insights into the regulatory mechanisms, tissue contexts, and genes affected by noncoding genetic variation associated with LOAD risk.

bioinformatics↗

bioRxiv2018

Genetic continuity in the last seven Millennia in human hepatitis B viruses

Hepatitis B virus (HBV) is a major human pathogen and yet the evolution history of HBV has largely remained uncertain. With a better theoretical understanding of genetic diversity, we here used a new method to examine the previously published ancient and present day HBV genomes. We identified an informative region in the HBV polymerase that is slow evolving and used it to study genetic distances among HBVs. Three ancient human HBV isolates from 4488-7074 years ago in Germany were identified as genotype G that is also presently common in the same country. We constructed a new phylogenetic tree of HBVs that placed genotype D as the most basal branch with an inferred age of ~20500 years, which is remarkably consistent with the worldwide distribution and a most parsimonious migration route of HBV genotypes today. These results help resolve the evolutionary history of HBV and provide a useful method for studying the phylogenetics of HBV and other viruses in general.

evolutionary biology↗

bioRxiv2018

Genetic control of the HDL proteome

High-density lipoproteins (HDL) are nanoparticles with >80 associated proteins, phospholipids, cholesterol and cholesteryl esters. A comprehensive genetic analysis of the regulation of proteome of HDL isolated from a panel of 100 diverse inbred strains of mice, Hybrid Mouse Diversity Panel (HMDP), revealed widely varied HDL protein levels across the strains. Some of this variation was explained by local, cis-acting regulation, termed cis-protein quantitative trait loci. Variations in apolipoprotein A-II and apolipoprotein C-3 affected the abundance of multiple HDL proteins indicating a coordinated regulation. We identified modules of co-varying proteins and define a protein-protein interaction network describing the protein composition of the naturally occurring subspecies of HDL in mice. Sterol efflux capacity varied up to 3-fold across the strains and HDL proteins displayed distinct correlation patterns with macrophage and ABCA1 specific cholesterol efflux capacity and cholesterol exchange, suggesting that subspecies of HDL participate in discrete functions. The baseline and stimulated sterol efflux capacity phenotypes associated with distinct QTLs with smaller effect size suggesting a multi genetic regulation. Our results highlight the complexity of HDL particles by revealing high degree of heterogeneity and intercorrelation, some of which is associated with functional variation, supporting the concept that HDL-cholesterol alone is not an accurate measure of HDLs properties such as protection against CAD.

systems biology↗

bioRxiv2018

Reverse genetic screen reveals that Il34 facilitates yolk sac macrophage distribution and seeding of the brain

Microglia are brain resident macrophages, which have specialized functions important in brain development and in disease. They colonize the brain in early embryonic stages, but few factors that drive the migration of yolk sac macrophages into the embryonic brain, or regulate their acquisition of specialized properties are currently known.\n\nHere, we present a CRISPR/Cas9-based in vivo reverse genetic screening pipeline to identify new regulators important for microglia development using zebrafish. Zebrafish larvae are particularly suitable due to their external development, transparency, high fecundity and conserved microglia features. We targeted putative microglia regulators, including signature genes and non-cell autonomous factors, by Cas9/gRNA-complex injections, followed by neutral red-based visualization of microglia. Microglia were quantified automatically in 3-day-old larvae using a software tool we called SpotNGlia. We identified that loss of function of the zebrafish homolog of the colony stimulating factor 1 receptor (CSF1R) ligand IL34, caused strongly reduced microglia numbers in early development. Previous studies on the role of the IL34 on microglia development in vivo were ambiguous. Our data, and a concurrent paper, show that in zebrafish, il34 is required during the earliest seeding of the brain by microglia progenitors. Our data also indicate that Il34 is required for distribution to other organs.\n\nPreviously, we showed that csf1ra and csf1rb double mutant zebrafish have no microglia. As there is a moderate effect of il34 on microglia development, relative to the effect csf1r, additional Csf1r-dependent signalling may be needed for establishment of the microglia network. In all, we identified il34 as a modifier of microglia colonization, by affecting distribution of yolk sac macrophages to target organs, validating our reverse genetic screening pipeline in zebrafish which can be used for the identification of additional regulators of microglia development.

developmental biology↗

bioRxiv2018

Genetic Circuits to Detect Nanomaterial Triggered Toxicity through Engineered Heat Shock Response Mechanism

Biocompatibility assessment of nanomaterials has been of great interest due to their potential toxicity. However, conventional biocompatibility tests are short of providing a fast toxicity report. We developed a whole cell based biosensor to track biocompatibility of nanomaterials with the aim of providing fast feedback for engineering nanomaterials with lower toxicity levels. We have engineered promoters of four heat shock response proteins. As an initial design a reporter coding gene was cloned to downstream of the promoter regions selected. Initial results indicated that native HSP promoter regions were not very promising to generate signals with low background signals. Introducing riboregulators to native promoters eliminated unwanted background signal almost entirely. Unfortunately, this approach also leads a decrease in expected sensor signal. Thus, a repression based genetic circuit, inspired from HSP mechanism of Mycobacterium tuberculosis was constructed. These genetic circuits can report the toxicity of Quantum Dot nanoparticles in one hour with high precision. Our designed nanoparticle toxicity sensors can provide quick reports which can lower the demand for additional experiments with more complex organisms.

synthetic biology↗

bioRxiv2018

Deconstructing cell-free extract preparation for in vitro activation of transcriptional genetic circuitry

Recent advances in cell-free gene expression (CFE) systems have enabled their use for a host of synthetic biology applications, particularly for rapid prototyping of genetic circuits designed as biosensors. Despite the proliferation of cell-free protein synthesis platforms, the large number of currently existing protocols for making CFE extracts muddles the collective understanding of how the method by which an extract is prepared affects its functionality. Specifically, a key goal toward developing cell-free biosensors based on native genetic regulators is activating the transcriptional machinery present in bacterial extracts for protein synthesis. However, protein yields from genes transcribed in vitro by the native Escherichia coli RNA polymerase are quite low in conventional crude extracts originally optimized for expression by the bacteriophage transcriptional machinery. Here, we show that cell-free expression of genes under bacterial {sigma}70 promoters is constrained by the rate of transcription in crude extracts and that processing the extract with a ribosomal run-off reaction and subsequent dialysis can alleviate this constraint. Surprisingly, these processing steps only enhance protein synthesis in genes under native regulation, indicating that the translation rate is unaffected. We further investigate the role of other common process variants on extract performance and demonstrate that bacterial transcription is inhibited by including glucose in the growth culture, but is unaffected by flash-freezing the cell pellet prior to lysis. Our final streamlined protocol for preparing extract by sonication generates extract that facilitates expression from a diverse set of sensing modalities including protein and RNA regulators. We anticipate that this work will clarify the methodology for generating CFE extracts that are active for biosensing and will encourage the further proliferation of cell-free gene expression technology for new applications.

synthetic biology↗

bioRxiv2018

Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients world-wide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention.

neuroscience↗

bioRxiv2018

Esterase Activity is Affected by Genetics, Age, Insecticide Exposure, and Viral Infection in the Honey Bee, Apis mellifera

Non-target impacts of insecticide treatments are a major public and environmental concern, particularly in contemporary beekeeping. Therefore, it is important to understand the physiological mechanisms contributing to insecticide sensitivity in honey bees. In the present studies, we sought to evaluate the role of esterases as the source of variation in insecticide sensitivity. To address this question, the following objectives were completed: 1) Evaluated esterase activity among honey bee stocks, 2) Assessed the correlation of esterase activity with changes in insecticide sensitivity with honey bee age, 3) Established if esterases can be used as a biomarker of insecticide exposure, and 4) Examined the effects of Varroa mite infestation and viral infection on esterase activity.\n\nResults indicated that honey bees have a dynamic esterase capacity that is influenced by genetic stock and age. However, there was no consistent connection of esterase activity with insecticide sensitivity across genetic stocks or with age, suggests other factors are more critical for determining insecticide sensitivity. The trend of increased esterase activity with age in honey bees suggests this physiological transition is consistent with enhanced metabolic rate with age. The esterase inhibition with naled but not phenothrin or clothianidin indicates that reduced esterase activity levels may only be reliable for sublethal doses of organophosphate insecticides. The observation that viral infection, but not Varroa mite infestation, reduced esterase activity shows viruses have extensive physiological impacts. Taken together, these data suggest that honey bee esterase activity toward these model substrates may not correlate well with insecticide sensitivity. Future studies include identification of esterase substrates and inhibitors that are better surrogates of insecticide detoxification in honey bees as well as investigation on the usefulness of esterase activity as a biomarker of pesticide exposure, and viral infection.

pharmacology and toxicology↗