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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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Genetic variants affecting plant size and chemical defenses jointly shape herbivory in Arabidopsis

Herbivorous insects exhibit strong feeding preferences when choosing among plant genotypes, yet experiments to map loci mediating plant susceptibility to herbivory rarely incorporate host choice. To address this gap, we applied genome-wide association (GWA) mapping to uncover genetic polymorphisms mediating damage from foraging insects (two populations of Scaptomyza flava) across a mixture of Arabidopsis thaliana genotypes in experimental enclosures. The effect of chemical defenses (glucosinolates) on herbivory depended on herbivore genotype. Unlike many studies that minimize the effects of host choice behavior, we also found a large effect of plant size on herbivory--likely through its effect on plant apparency--that was independent of herbivore genotype. These herbivory-associated loci are polymorphic at fine spatial scales, and thus have potential to shape variation in herbivory within natural populations. We also show that the polymorphism with the largest effect on herbivory underlies adaptive latitudinal variation in Arabidopsis plant size across Europe. Overall, our results provide genetic support for ecological observations that variation in both chemical defenses and non-canonical defense traits (e.g., plant size and phenology) jointly shapes plant-herbivore interactions.

plant biology

Is obesity a genetic disease? Human obese transcriptome analysis in monozygotic twins

Obesity is a pandemic disease with a critical increase in childhood. An important unanswered question is to understand if this disease is due to genetic causes or to the life-style of the subjects. To address this question, we have analyzed if monozygotic twins show the same robust transcriptomic signature (5{sigma}, as for the Higgs Boson) that we have recently revealed in obese subjects. Our results show that our signature correlates with BMI in paired transcriptomes of monozygotic twins, suggesting that the signature does not reflect underlying genetic causes.

systems biology

Robust and Bright Genetically Encoded Fluorescent Markers for Highlighting Structures and Compartments in Mammalian Cells

To increase our understanding of the inner working of cells, there is a need for specific markers to identify biomolecules, cellular structures and compartments. One type of markers comprises genetically encoded fluorescent probes that are linked with protein domains, peptides and/or signal sequences. These markers are encoded on a plasmid and they allow straightforward, convenient labeling of cultured mammalian cells by introducing the plasmid into the cells. Ideally, the fluorescent marker combines favorable spectroscopic properties (brightness, photostability) with specific labeling of the structure or compartment of interest. Here, we report our ongoing efforts to generate robust and bright genetically encoded fluorescent markers for highlighting structures and compartments in living cells. The plasmids are distributed by addgene: https://www.addgene.org/browse/article/28189953/ O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/160374v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@67f3aaorg.highwire.dtl.DTLVardef@ae2235org.highwire.dtl.DTLVardef@47f729org.highwire.dtl.DTLVardef@b3c9d1_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology

Why are tropical mountain passes ‘low’ for some species? Genetic and stable-isotope tests for differentiation, migration, and expansion in elevational generalist songbirds

Most tropical bird species have narrow elevational ranges, likely reflecting climatic specialization. This is consistent with Janzens Rule, the tendency for mountain passes to be effectively higher in the tropics. Hence, those few tropical species that occur across broad elevational gradients raise questions. Are they being sundered by diversifying selection along the gradient? Does elevational movement cause them to resist diversification or specialization? Have they recently expanded, suggesting that elevational generalism is short-lived in geological time? Here we tested for differentiation, movement, and expansion in four elevational generalist songbird species on the Andean west slope. We used morphology and mtDNA to test for genetic differentiation between high- and low-elevation populations. Morphology differed for House Wren (Troglodytes aedon) and Hooded Siskin (Spinus magellanicus), but not for Cinereous Conebill (Conirostrum cinereum) and Rufous-collared Sparrow (Zonotrichia capensis), respectively. mtDNA was structured by elevation only in Z. capensis. To test for elevational movements, we measured hydrogen isotope ({delta}2H) values of metabolically inert feathers and metabolically active liver. {delta}2H data indicated elevational movements by two tree- and shrub-foraging species with moderate-to-high vagility (C. cinereum and S. magellanicus), and sedentary behavior by two terrestrial-foraging species with low-to-moderate vagility (T. aedon and Z. capensis). In S. magellanicus, elevational movements and lack of mtDNA structure contrast with striking morphological divergence, suggesting strong diversifying selection on body proportions across the [~]50 km gradient. All species except C. cinereum exhibited mtDNA-haplotype variation consistent with recent population expansion across the elevational gradient.In sum,three out of four elevational generalist species underwent genetic divergence despite gene flow, two of four make seasonal elevational movements, and three of four have recently expanded. In different ways, each species defies the tendency for tropical birds to have long-term stable distributions and sedentary habits. We conclude that tropical elevational generalism is rare due to evolutionary instability.

evolutionary biology

A central role for boom-bust cycles in maintaining genetic variation in fluctuating environments

The long-running debate about the role of selection in maintaining genetic variation has been given new impetus by the discovery of hundreds of seasonally oscillating polymorphisms in wild Drosophila, possibly stabilized by an alternating summer-winter selection regime. Historically there has been skepticism about the potential of temporal variation to balance polymorphism, because selection must be strong to have a meaningful stabilizing effect -- unless dominance also varies over time ("reversal of dominance"). Here we develop a simplified model of seasonally variable selection that simultaneously incorporates four different stabilizing mechanisms, including two genetic mechanisms ("cumulative overdominance" and reversal of dominance), as well as ecological "storage" ("protection from selection" and boom-bust demography). We use our model to compare the stabilizing effects of these mechanisms. Although reversal of dominance has by far the greatest stabilizing effect, we argue that the three other mechanisms could also stabilize polymorphism under plausible conditions, particularly when all three are present. With many loci subject to diminishing returns epistasis, reversal of dominance stabilizes many alleles of small effect. This makes the combination of the other three mechanisms, which are incapable of stabilizing small effect alleles, a better candidate for stabilizing the detectable frequency oscillations of large effect alleles.

evolutionary biology

Genome expansion and lineage-specific genetic innovations in the world’s largest organisms (Armillaria)

Armillaria species are both devastating forest pathogens and some of the largest terrestrial organisms on Earth. They forage for hosts and achieve immense colony sizes using rhizomorphs, root-like multicellular structures of clonal dispersal. Here, we sequenced and analyzed genomes of four Armillaria species and performed RNA-Seq and quantitative proteomic analysis on seven invasive and reproductive developmental stages of A. ostoyae. Comparison with 22 related fungi revealed a significant genome expansion in Armillaria, affecting several pathogenicity-related genes, lignocellulose degrading enzymes and lineage-specific genes likely involved in rhizomorph development. Rhizomorphs express an evolutionarily young transcriptome that shares features with the transcriptomes of fruiting bodies and vegetative mycelia. Several genes show concomitant upregulation in rhizomorphs and fruiting bodies and shared cis-regulatory signatures in their promoters, providing genetic and regulatory insights into complex multicellularity in fungi. Our results suggest that the evolution of the unique dispersal and pathogenicity mechanisms of Armillaria might have drawn upon ancestral genetic toolkits for wood-decay, morphogenesis and complex multicellularity.

evolutionary biology

The dynamics of adaptive genetic diversity during the early stages of clonal evolution

The dynamics of genetic diversity in large clonally-evolving cell populations are poorly understood, despite having implications for the treatment of cancer and microbial infections. Here, we combine barcode lineage tracking, sequencing of adaptive clones, and mathematical modelling of mutational dynamics to understand diversity changes during experimental evolution. We find that, despite differences in beneficial mutational mechanisms and fitness effects between two environments, early adaptive genetic diversity increases predictably, driven by the expansion of many single-mutant lineages. However, a crash in diversity follows, caused by highly-fit double-mutants fed from exponentially growing single-mutants, a process closely related to the classic Luria-Delbruck experiment. The diversity crash is likely to be a general feature of clonal evolution, however its timing and magnitude is stochastic and depends on the population size, the distribution of beneficial fitness effects, and patterns of epistasis.

evolutionary biology

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila

Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation. To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population. Transcriptome and respiration measurements revealed extensive metabolic rewiring after only [~]60 generations in a hot environment. Analysis of genome-wide polymorphisms identified two interacting selection targets, Sestrin and SNF4A{gamma}, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation. Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because SNF4A{gamma} also exhibits clinal variation in various Drosophila species, we suggest that this large effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.

evolutionary biology

An atlas of genetic associations in UK Biobank

Genome-wide association studies have revealed many loci contributing to the variation of complex traits, yet the majority of loci that contribute to the heritability of complex traits remain elusive. Large study populations with sufficient statistical power are required to detect the small effect sizes of the yet unidentified genetic variants. However, the analysis of huge cohorts, like UK Biobank, is complicated by incidental structure present when collecting such large cohorts. For instance, UK Biobank comprises 107,162 third degree or closer related participants. Traditionally, GWAS have removed related individuals because they comprised an insignificant proportion of the overall sample size, however, removing related individuals in UK Biobank would entail a substantial loss of power. Furthermore, modelling such structure using linear mixed models is computationally expensive, which requires a computational infrastructure that may not be accessible to all researchers. Here we present an atlas of genetic associations for 118 non-binary and 599 binary traits of 408,455 related and unrelated UK Biobank participants of White-British descent. Results are compiled in a publicly accessible database that allows querying genome-wide association summary results for 623,944 genotyped and HapMap2 imputed SNPs, as well downloading whole GWAS summary statistics for over 30 million imputed SNPs from the Haplotype Reference Consortium panel. Our atlas of associations (GeneATLAS, http://geneatlas.roslin.ed.ac.uk) will help researchers to query UK Biobank results in an easy way without the need to incur in high computational costs.

genomics

A minimally sufficient model for rib proximal-distal patterning based on genetic analysis and agent-based simulations

For decades, the mechanism of skeletal patterning along a proximal-distal axis has been an area of intense inquiry. Here we examine the development of the ribs, simple structures that in most terrestrial vertebrates consist of two skeletal elements-- a proximal bone and a distal cartilage portion. While the ribs have been shown to arise from the somites, little is known about how the two segments are specified. During our examination of genetically modified mice, we discovered a series of progressively worsening phenotypes that could not be easily explained. Here, we combine genetic analysis of rib development with agent-based simulations to conclude that proximal-distal patterning and outgrowth could occur based on simple rules. In our model, specification occurs during somite stages due to varying Hedgehog protein levels, while later expansion refines the pattern. This framework is broadly applicable for understanding the mechanisms of skeletal patterning along a proximal-distal axis.

developmental biology

Genetic fingerprinting of salmon louse (Lepeophtheirus salmonis) populations in the North-East Atlantic using a random forest classification approach

Caligid sea lice represent a significant threat to salmonid aquaculture worldwide. Lepeophtheirus salmonis is the predominant species that occurs in the Northern Hemisphere. Dispersal of sea lice between marine aquaculture sites and geographic regions is thought to occur rapidly via planktonic transport of larvae. Population genetic analyses have consistently shown minimal population genetic structure in North Atlantic L. salmonis, frustrating efforts to track louse populations, improve targeted control measures and understand local adaption to environmental conditions. The aim of this study was to test the power of reduced representation library sequencing (IIb-RAD sequencing) coupled with random forest machine learning algorithms to define markers for fine-scale discrimination of louse populations. We identified 1286 robustly supported SNPs among four L. salmonis populations from Ireland (N=2, 27 individuals), Scotland (N=1, 11 individuals) and North Norway (N=1, 12 individuals). Weak global structure (FSC = 0.018, p<0.0001) and only one significant pairwise FST comparison was observed (Scotland vs Kenmare Bay, (FST = 0.018, p<0.0001)) using all 1286 SNPs. The application of a random forest machine-learning algorithm identified 98 discriminatory SNPs that dramatically improved population assignment (DAPC assignment probability = 1), increased global Fsc = 0.098, (p<0.0001) and resulted in pairwise comparisons that all showed highly significant Fst-values (range = 0.081 - 0.096, p<0.0001). Out of 19 SNPs found to be under directional selection between populations, 12 corresponded to the discriminatory SNPs identified using random forest. Taken together our data suggest that L. salmonis SNP diversity exists with which it is possible to discriminate differences between nearby populations given suitable marker selection approaches, and that such differences might have an adaptive basis. We discuss these data in light of sea lice adaption to anthropogenic and environmental pressures as well as novel approaches to track and predict sea louse dispersal.

ecology

Genetic and real-world clinical data, combined with empirical validation, nominate JAK-STAT signalling as a target for Alzheimer’s Disease therapeutic development

As Genome Wide Association Studies (GWAS) have grown in size, the number of genetic variants that have been nominated for an increasing number of diseases has correspondingly increased. Despite this increase in the number of associated SNPs per disease, their biological interpretation has in many cases remained elusive. To address this, we have combined GWAS results with an orthogonal source of evidence, namely real-world, routinely collected clinical data from more than 6 million patients in order to drive target nomination. First we show that when examined at a pathway level, analysis of all GWAS studies groups Alzheimers disease (AD) in a cluster with disorders of immunity and inflammation. Using clinical data we show that the degree of comorbidity of these diseases with AD correlates with the strength of their genetic association with molecular participants in the JAK-STAT pathway. Using four independent open-science datasets we then find evidence for altered regulation of JAK-STAT pathway genes in AD. Finally, we use both in vitro and in vivo rodent models to demonstrate that A{beta} induces gene expression of key drivers of this pathway, providing experimental evidence validating these data-driven observations. These results therefore nominate JAK-STAT anomalies as a prominent aetiopathological event in AD and hence potential target for therapeutic development, and moreover demonstrate a de-novo multi-modal approach to derive information from rapidly increasing genomic datasets.\n\nOne Sentence SummaryCombining evidence from genome wide association studies, real-world clinical and cohort molecular data together with experimental studies in rodent model systems nominates JAK-STAT signaling as an aetiopathological event in Alzheimers disease

bioinformatics

Functional characterization of 3D-protein structures informed by human genetic diversity

Sequence variation data of the human proteome can be used to analyze 3-dimensional (3D) protein structures to derive functional insights. We used genetic variant data from nearly 150,000 individuals to analyze 3D positional conservation in 4,390 protein structures using 481,708 missense and 264,257 synonymous variants. Sixty percent of protein structures harbor at least one intolerant 3D site as defined by significant depletion of observed over expected missense variation. We established an Angstrom-scale distribution of annotated pathogenic missense variants and showed that they accumulate in proximity to the most intolerant 3D sites. Structural intolerance data correlated with experimental functional read-outs in vitro. The 3D structural intolerance analysis revealed characteristic features of ligand binding pockets, orthosteric and allosteric sites. The identification of novel functional 3D sites based on human genetic data helps to validate, rank or predict drug target binding sites in vivo.

genomics

Likelihood analysis of population genetic data under coalescent models: computational and inferential aspects

Likelihood methods are being developed for inference of migration rates and past demographic changes from population genetic data. We survey an approach for such inference using sequential importance sampling techniques derived from coalescent and diffusion theory. The consistent application and assessment of this approach has required the re-implementation of methods often considered in the context of computer experiments methods, in particular of Kriging which is used as a smoothing technique to infer a likelihood surface from likelihoods estimated in various parameter points, as well as reconsideration of methods for sampling the parameter space appropriately for such inference. We illustrate the performance and application of the whole tool chain on simulated and actual data, and highlight desirable developments in terms of data types and biological scenarios.\n\nResumeDiverses approches ont ete developpees pour linference des taux de migration et des changements demo-graphiques passes a partir de la variation genetique des populations. Nous decrivons une de ces approches utilisant des techniques dechantillonnage pondere sequentiel, fondees sur la modelisation par approches de coalescence et de diffusion de levolution de ces polymorphismes. Lapplication et levaluation systematique de cette approche ont requis la re-implementation de methodes souvent considerees pour lanalyse de fonctions simulees, en particulier le krigeage, ici utilise pour inferer une surface de vraisemblance a partir de vraisemblances estimees en differents points de lespace des parametres, ainsi que des techniques dechantillonage de ces points. Nous illustrons la performance et lapplication de cette serie de methodes sur donnees simulees et reelles, et indiquons les ameliorations souhaitables en termes de types de donnees et de scenarios biologiques.\n\nMots-cleshistoire demographique, processus de coalescence, importance sampling, genetic polymorphism\n\nAMS 2000 subject classifications92D10, 62M05, 65C05

evolutionary biology

Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision

Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety of biological contexts involving in AS, such as development and diseases. We assembled splicing (epi)genetic code, DeepCode, for human embryonic stem cell (hESC) differentiation by integrating heterogeneous features of genomic sequences, 16 histone modifications with a multi-label deep neural network. With the advantages of epigenetic features, DeepCode significantly improves the performance in predicting the splicing patterns and their changes during hESC differentiation. Meanwhile, DeepCode reveals the superiority of epigenomic features and their dominant roles in decoding AS patterns, highlighting the necessity of including the epigenetic properties when assembling a more comprehensive splicing code. Moreover, DeepCode allows the robust predictions across cell lineages and datasets. Especially, we identified a putative H3K36me3-regulated AS event leading to a nonsense-mediated mRNA decay of BARD1. Reduced BARD1 expression results in the attenuation of ATM/ATR signalling activities and further the hESC differentiation. These results suggest a novel candidate mechanism linking histone modifications to hESC fate decision. In addition, when trained in different contexts, DeepCode can be expanded to a variety of biological and biomedical fields.

bioinformatics

High-Throughput Identification of Genetic Variation Impact on pre-mRNA Splicing Efficiency

AbstractUnderstanding the functional impact of genomic variants is a major goal of modern genetics and personalized medicine. Although many synonymous and non-coding variants act through altering the efficiency of pre-mRNA splicing, it is difficult to predict how these variants impact pre-mRNA splicing. Here, we describe a massively parallel approach we used to test the impact of 2,059 human genetic variants spanning 110 alternative exons on pre-mRNA splicing. This method yields data that reinforces known mechanisms of pre-mRNA splicing, can rapidly identify genomic variants that impact pre-mRNA splicing, and will be useful for increasing our understanding of genome function.

genomics

Genetic diversity and mother-child overlap of the gut associated microbiota determined by reduced genome sequencing

The genetic diversity and sharing of the mother-child associated microbiota remain largely unexplored. This severely limits our functional understanding of gut microbiota transmission patterns. The aim of our work was therefore to use a novel reduced metagenome sequencing in combination with shotgun and 16S rRNA gene sequencing to determine both the metagenome genetic diversity and the mother-to-child sharing of the microbiota. For a cohort of 17 mother-child pairs we found an increase of the collective metagenome size from about 100 Mbp for 4-day-old children to about 500 Mbp for mothers. The 4-day-old children shared 7% of the metagenome sequences with the mothers, while the metagenome sequence sharing was more than 30% among the mothers. We found 15 genomes shared across more than 50% of the mothers, of which 10 belonged to Clostridia. Only Bacteroides showed a direct mother-child association, with B. vulgatus being abundant in both 4-day-old children and mothers. In conclusion, our results support a common pool of gut bacteria that are transmitted from adults to infants, with most of the bacteria being transmitted at a stage after delivery.

microbiology

Comparative analysis of 24 chloroplast genomes yields highly informative genetic markers for the Brazil nut family (Lecythidaceae)

O_LIPremise of the study: The tropical tree family Lecythidaceae has enormous ecological and economic importance in the Amazon basin. Lecythidaceae species can be difficult to identify without molecular data, however, and phylogenetic relationships within and among the most diverse genera are poorly resolved.\nC_LIO_LIMethods: To develop informative genetic markers for Lecythidaceae, we used genome skimming to assemble de novo the full plastome of the Brazil nut tree (Bertholletia excelsa) and 23 other Lecythidaceae species. Indices of nucleotide diversity and phylogenetic signal were used to identify regions suitable for genetic marker development.\nC_LIO_LIResults: The B. excelsa plastome contained 160,472 bp and was arranged in a quadripartite structure. Using the 24 plastome alignments, we developed primers for 10 coding and non-coding DNA regions containing exceptional nucleotide diversity and phylogenetic signal. We additionally developed 19 chloroplast simple sequence repeats (cpSSRs) for population-level studies.\nC_LIO_LIDiscussion: The coding region ycf1 and the spacer rpl16-rps3 outperformed plastid DNA markers previously used for barcoding and phylogenetics. Used in a phylogenetic analysis, the matrix of 24 plastomes showed with 100% bootstrap support that Lecythis and Eschweilera are polyphyletic. The plastomes and primers presented in this study will facilitate a broad array of ecological and evolutionary studies in Lecythidaceae.\nC_LI

evolutionary biology