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Identification of environmental and genetic factors important for Cryptococcus neoformans titan cell formation using new in vitro inducing conditions

The pathogenic fungus Cryptococcus neoformans exhibits morphological changes in cell size during lung infection, producing both typical size 5 to 7 {micro}m cells and large titan cells (> 10 {micro}m and up to 100 {micro}m). We found and optimized in vitro conditions that produce titan cells in order to identify the ancestry of titan cells, the environmental determinants, and the key gene regulators of titan cell formation. Titan cells generated in vitro harbor the main characteristics of titan cells produced in vivo including their large cell size (>10 {micro}m), polyploidy with a single nucleus, large vacuole, dense capsule, and thick cell wall. Here we show titan cells derived from the enlargement of progenitor cells in the population independent of yeast growth rate. Change in the incubation medium, hypoxia, nutrient starvation and low pH were the main factors that trigger titan cell formation, while quorum sensing factors like the initial inoculum concentration, pantothenic acid, and the quorum sensing peptide Qsp1p also impacted titan cell formation. Inhibition of ergosterol, protein and nucleic acid biosynthesis altered titan cell formation, as did serum, phospholipids and anti-capsular antibodies in our settings. We explored genetic factors important for titan cell formation using three approaches. Using H99-derivative strains with natural genetic differences, we showed that titan cell formation was dependent on LMP1 and SGF29 genes. By screening a gene deletion collection, we also confirmed that GPR4/5-RIM101, and CAC1 genes were required to generate titan cells and that the PKR1, TSP2, USV101 genes negatively regulated titan cell formation. Furthermore, analysis of spontaneous Pkr1 loss-of-function clinical isolates confirmed the important role of the Pkr1 protein as a negative regulator of titan cell formation. Through development of a standardized and robust in vitro assay, our results provide new insights into titan cell biogenesis with the identification of multiple important factors/pathways.\n\nAuthor SummaryCryptococcus neoformans is a yeast that is capable of morphological change upon interaction with the host. Particularly, in the lungs of infected mice, a subpopulation of yeast enlarges, producing cells up to 100 {micro}m in cell body diameter - referred to as titan cells. Along with their large size, the titan cells have other unique characteristics such as thickened cell wall, dense capsule, polyploidization, large vacuole with peripheral nucleus and cellular organelles. The generation of a large number of such cells outside the lungs of mice has been described but was not reproducible nor standardized. Here we report standardized, reproducible, robust conditions for generation of titan cells and explored the environmental and genetic factors underlying the genesis of these cells. We showed that titan cells were generated upon stresses such as change in the incubation medium, nutrient deprivation, hypoxia and low pH. Using collections of well characterized reference strains and clinical isolates, we validated with our model that the cAMP/PKA/Rim101 pathway is a major genetic determinant of titan cell formation. This study opens the way for a more comprehensive picture of the ontology of morphological changes in Cryptococcus neoformans and its impact on pathobiology of this deadly pathogen.

microbiology

Chromatin accessibility profiling uncovers genetic- and T2D disease state-associated changes in cis-regulatory element use in human islets

Genetic and environmental factors both contribute to islet dysfunction and failure, resulting in type 2 diabetes (T2D). The islet epigenome integrates these cues and can be remodeled by genetic and environmental variation. However, our knowledge of how genetic variants and T2D disease state alter human islet chromatin landscape and cis-regulatory element (RE) use is lacking. To fill this gap, we profiled and analyzed human islet chromatin accessibility maps from 19 genotyped individuals (5 with T2D) using ATAC-seq technology. Chromatin accessibility quantitative trait locus (caQTL) analyses identified 3001 sequence variants (FDR<10%) altering putative cis-RE use/activity. Islet caQTL were significantly and specifically enriched in islet stretch enhancers and islet-specific transcription factor binding motifs, such as FOXA2, NKX6.1, RFX5/6 and PDX1. Importantly, these analyses identified putative functional single nucleotide variants (SNVs) in 13 T2D-associated GWAS loci, including those previously associated with altered ZMIZ1, MTNR1B, RNF6, and ADCY5 islet expression, and linked the risk alleles to increased (n=8) or decreased (n=5) islet chromatin accessibility. Luciferase reporter assays confirmed allelic differences in cis-RE activity for 5/9 caQTL sequences tested, including a T2D-associated SNV in the IL20RA locus. Comparison of T2D and non-diabetic islets revealed 1882 open chromatin sites exhibiting T2D-associated chromatin accessibility changes (FDR<10%). Together, this study provides new insights into genetic variant and T2D disease state effects on islet cis-RE use and serves as an important resource to identify putative functional variants in T2D-and islet dysfunction-associated GWAS loci and link their risk allele to in vivo loss or gain of chromatin accessibility.

genomics

Detection of functional protein domains by unbiased genome-wide forward genetic screening

Genetic and chemo-genetic interactions have played key roles in elucidating the molecular mechanisms by which certain chemicals perturb cellular functions. Many studies have employed gene knockout collections or gene disruption/depletion strategies to identify routes for evolving resistance to chemical agents. By contrast, searching for point-mutational genetic suppressors that can identify separation- or gain-of-function mutations, has been limited even in simpler, genetically amenable organisms such as yeast, and has not until recently been possible in mammalian cell culture systems. Here, by demonstrating its utility in identifying suppressors of cellular sensitivity to the drugs camptothecin or olaparib, we describe an approach allowing systematic, large-scale detection of spontaneous or chemically-induced suppressor mutations in yeast and in haploid mouse embryonic stem cells in a short timeframe, and with potential applications in essentially any other haploid system. In addition to its utility for molecular biology research, this protocol can be used to identify drug targets and to predict mechanisms leading to drug resistance. Mapping suppressor mutations on the primary sequence or three-dimensional structures of protein suppressor hits provides insights into functionally relevant protein domains, advancing our molecular understanding of protein functions, and potentially helping to improve drug design and applicability.

molecular biology

Pydigree: a python library for manipulation and forward-time simulation and of genetic datasets

The development of software for working with data from population genetics or genetic epidemiology often requires substantial time spent implementing common procedures. Pydigree is a cross-platform Python 3 library that contains efficient, user friendly implementations for many of these common functions, and support for input from common file formats. Developers can combine the functions and data structures to rapidly implement programs handling genetic data. Pydigree presents a useful environment for development of applications for genetic data or rapid prototyping before reimplementation in a higher-performance language.\n\nPydigree is freely available under an open source license. Stable sources can be found in the Python Package Index at https://pypi.python.org/pypi/pydigree/, and development sources can be downloaded at https://github.com/jameshicks/pydigree/

bioinformatics

Gene regulatory network architecture in different developmental contexts influences the genetic basis of morphological evolution

Convergent phenotypic evolution is often caused by recurrent changes at particular nodes in the underlying gene regulatory networks (GRNs). The genes at such evolutionary hotspots are thought to maximally affect the phenotype with minimal pleiotropic consequences. This has led to the suggestion that if a GRN is understood in sufficient detail, the path of evolution may be predictable. The repeated evolutionary loss of larval trichomes among Drosophila species is caused by the loss of shavenbaby (svb) expression. svb is also required for development of leg trichomes, but the evolutionary gain of trichomes in the naked valley on T2 femurs in Drosophila melanogaster is caused by the loss of microRNA-92a (miR-92a) expression rather than changes in svb. We compared the expression and function of components between the larval and leg trichome GRNs to investigate why the genetic basis of trichome pattern evolution differs in these developmental contexts. We found key differences between the two networks in both the genes employed, and in the regulation and function of common genes. These differences in the GRNs reveal why mutations in svb are unlikely to contribute to leg trichome evolution and how instead miR-92a represents the key evolutionary switch in this context. Our work shows that variability in GRNs across different developmental contexts, as well as whether a morphological feature is lost versus gained, influence the nodes at which a GRN evolves to cause morphological change. Therefore, our findings have important implications for understanding the pathways and predictability of evolution.\n\nAuthor SummaryA major goal of biology is to identify the genetic cause of organismal diversity. Convergent evolution of traits is often caused by changes in the same genes - evolutionary hotspots. shavenbaby is a hotspot for larval trichome loss in Drosophila, however microRNA-92a underlies the gain of leg trichomes. To understand this difference in the genetics of phenotypic evolution, we compared the expression and function of genes in the underlying regulatory networks. We found that the pathway of evolution is influenced by differences in gene regulatory network architecture in different developmental contexts, as well as by whether a trait is lost or gained. Therefore, hotspots in one context may not readily evolve in a different context. This has important implications for understanding the genetic basis of phenotypic change and the predictability of evolution.

evolutionary biology

Stability in the genetic structure of a Zymoseptoria tritici population from epidemic to interepidemic stages at a small spatial scale

Subpopulations of the wheat pathogen Zymoseptoria tritici (26 sample groups composed of 794 strains) were collected in two nearby wheat fields in the Paris basin, during both epidemic and inter-epidemic periods of three successive years (2009-2013). In addition to the type of inoculum (ascospores vs. pycnidiospores), the alternative presence of wheat debris allowed taking into account its putative origin (local vs. distant). We used a molecular epidemiology approach, based on population genetic indices derived from SSR marker analysis, to describe putative changes in the structure and genotypic diversity of these subpopulations over three years, at a spatiotemporal scale consistent with epidemiological observations. Genetic structure was stable over time (within and between years) and between fields. All subpopulations displayed very high levels of gene and genotypic diversity. The low levels of linkage disequilibrium and the very low clonal fraction at all stages were consistent with the regular occurrence of sexual reproduction in the two fields. A significant increase of the MAT1-1/MAT1-2 ratio was observed over the course of the epidemics, suggesting a competitive advantage of MAT1-1 strains consistently with their greater pathogenicity reported in the literature. Finally, we found that the period, the type of inoculum and its putative origin had little effect on the short term evolution of the local population of Z. tritici. Fungal population size and diversity are apparently large enough to prevent genetic drift at this fine spatiotemporal scale, and more likely short distance migration contributes strongly to the stabilization of genetic diversity among and within plots.

epidemiology

Multivariate analysis reveals environmental and genetic determinants of element covariation in the maize grain ionome

Plants obtain elements from the soil through genetic and biochemical pathways responsive to physiological state and environment. Most perturbations affect multiple elements which leads the ionome, the full complement of mineral nutrients in an organism, to vary as an integrated network rather than a set of distinct single elements. To examine the genetic basis of covariation in the accumulation of multiple elements, we analyzed maize kernel ionomes from Intermated B73 x Mo17 (IBM) recombinant inbred populations grown in 10 environments. We compared quantitative trait loci (QTL) determining single-element variation to QTL that predict variation in principal components (PCs) of multiple-element covariance. Single-element and multivariate approaches detected partially overlapping sets of loci. In addition to loci co-localizing with single-element QTL, multivariate traits within environments were controlled by loci with significant multi-element effects not detectable using single-element traits. Gene-by-environment interactions underlying multiple-element covariance were identified through QTL analyses of principal component models of ionome variation. In addition to interactive effects, growth environment had a profound effect on the elemental profiles and multi-element phenotypes were significantly correlated with specific environmental variables.\n\nAuthor SummaryA multivariate approach to the analysis of element accumulation in the maize kernel shows that elements are not regulated independently. By describing relationships between element accumulation we identified new genetic loci invisible to single-element approaches. The mathematical combinations of elements distinguish groups of plants based on environment, demonstrating that observed variation derives from interactions between genetically controlled factors and environmental variables. These results suggest that successful application of ionomics to improve human nutrition and plant productivity requires simultaneous consideration of multiple-element effects and variation of such effects in response to environment.

plant biology

Exploring the genetic correlations of antisocial behavior and life history traits

Prior evolutionary theory provided reason to suspect that measures of development and reproduction would be correlated with antisocial behaviors in human and non-human species. Behavioral genetics has revealed that most quantitative traits are heritable, suggesting that these phenotypic correlations may share genetic etiologies. We use GWAS data to estimate the genetic correlations between various measures of reproductive development (N= 52,776 - 318,863) and antisocial behavior (N= 31,968). Our genetic correlation analyses demonstrate that alleles associated with higher reproductive output (number of children ever born, rg=0.50, p=.0065) were positively correlated with alleles associated with antisocial behavior, whereas alleles associated with more delayed reproductive onset (age of first birth, rg=-.64, p=.0008) were negatively associated with alleles linked to antisocial behavior. Ultimately, these findings coalesce with evolutionary theories suggesting that increased antisocial behaviors may partly represent a faster life history approach, which may be significantly calibrated by genes.

genomics

Genetic factors and age are the strongest predictors of humoral immune responses to common pathogens and vaccines

IntroductionHumoral immune responses to infectious agents or vaccination vary substantially among individuals, and many of the factors responsible for this variability remain to be defined. Current evidence suggests that human genetic variation influences (i) serum immunoglobulin levels, (ii) seroconversion rates, and (iii) intensity of antigen-specific immune responses. Here, we evaluate the impact of intrinsic (age and sex), environmental and genetic factors on the variability of humoral response to common pathogens and vaccines.\n\nMethodsWe characterized the serological response to 15 antigens from common human pathogens or vaccines, in an age- and sex-stratified cohort of 1,000 healthy individuals (Milieu Interieur cohort). Using clinical-grade serological assays, we measured total IgA, IgE, IgG and IgM levels, as well as qualitative (serostatus) and quantitative IgG responses to cytomegalovirus, Epstein-Barr virus, herpes simplex virus 1 & 2, varicella zoster virus, Helicobacter pylori, Toxoplasma gondii, influenza A virus, measles, mumps, rubella, and hepatitis B virus. Following genome-wide genotyping of single nucleotide polymorphisms and imputation, we examined associations between ~5 million genetic variants and antibody responses using single marker and gene burden tests.\n\nResults and discussionWe identified age and sex as important determinants of humoral response, with older individuals and women having higher rates of seropositivity for most antigens. Genome-wide association studies revealed significant associations between variants in the human leucocyte antigen (HLA) class II region on chromosome 6 and anti-EBV and anti-rubella IgG levels. We used HLA imputation to fine map these associations to amino acid variants in the peptide-binding groove of HLA-DR{beta}1 and HLA-DP{beta}1, respectively. We also observed significant associations for total IgA levels with two loci on chromosome 2 and with specific KIR-HLA combinations.\n\nConclusionsUsing extensive serological testing and genome-wide association analyses in a well-characterized cohort of healthy individuals, we demonstrate that age, sex and specific human genetic variants contribute to inter-individual variability in humoral response. By highlighting genes and pathways implicated in the normal antibody response to frequently encountered antigens, these findings provide a basis to better understand disease pathogenesis.

genomics

Genotyping-by-sequencing supports a genetic basis for alpine wing-reduction in a New Zealand stonefly

Wing polymorphism is a prominent feature of numerous insect groups, but the genomic basis for this diversity remains poorly understood. Wing reduction is a commonly observed trait in many species of stoneflies, particularly in cold or alpine environments. The widespread New Zealand stonefly Zelandoperla fenestrata species group (Z. fenestrata, Z. tillyardi, Z. pennulata) contains populations ranging from long-winged (macropterous) to vestigial-winged (micropterous), with the latter phenotype typically associated with high altitudes. The presence of flightless forms on numerous mountain ranges, separated by lowland fully winged populations, suggests wing reduction has occurred multiple times. We use Genotyping by Sequencing (GBS) to test for genetic differentiation between fully winged (n=62) and vestigial-winged (n=34) individuals, sampled from a sympatric population of distinct wing morphotypes, to test for a genetic basis for wing morphology. We found no population genetic differentiation between these two morphotypes across 6,843 SNP loci, however we did detect several outlier loci that strongly differentiated morphotypes across independent tests. This indicates small regions of the genome are likely to be highly differentiated between morphotypes, indicating a genetic basis for morphotype differentiation. These results provide a clear basis for ongoing genomic analysis to elucidate critical regulatory pathways for wing development in Pterygota.

evolutionary biology

Protein pheromone MUP20/Darcin is a vector and target of indirect genetic effects in mice.

Social behavior in animals is an adaptive process influenced by environmental factors and direct and indirect genetic effects. Indirect genetic effects (IGEs) include mechanisms by which individuals of particular genotypes can influence the behavioral phenotypes and genotypes (via modulated patterns of gene expression) of other individuals with different genotypes. In groups of adult mice, IGEs can be unidirectional, from one genotype to the other, or bidirectional, resulting in a homogenization of the behavioral phenotypes within the group. Critically, it has been theorized that IGEs constitute a large fitness target on which deleterious mutations can have pleiotropic effects, meaning that individuals carrying certain behavior-altering mutations can impose the fitness costs of those mutations on others comprising the broader social genome. Experimental data involving a mouse model support the existence of these IGE-amplified fitness losses; however, the underlying biological mechanisms that facilitate these remain unknown. In a mouse model of IGEs, we demonstrate that the Major Urinary Protein 20 pheromone, also called Darcin, produced by mice lacking the adhesion protein Neuroligin-3 acts as a vector to deleteriously modify the social behavior of wild-type mice. Additionally, we showed that lack of social interest on the part of Neuroligin-3 knockout mice is independent of their environment. These findings reveal a new role for mammalian pheromones in mediating the externalization of social deficits from one individual to others comprising the population through IGEs.\n\nAuthor SummaryIndirect genetic effects (IGEs) are mechanisms by which individuals of particular genotypes can influence the behavioral phenotype of individuals of different genotypes, sometimes disruptively, in instances where one member of the population carriers a deleterious behavior altering variant. Although disruptive IGEs have been demonstrated in mice, its underlying molecular and genetic mechanisms remain unknown. Using an IGEs mouse model, we demonstrated that the pheromone protein Major Urinary Protein 20, also named Darcin, is as a vector and target of social epistasis a specific type of IGEs. This finding reveals a new function for mammalian pheromones in mediating social epistasis to degrade group social behavior.

animal behavior and cognition

Epigenomic convergence of genetic and immune risk factors in autism brain

Neurodevelopmental disorders (NDDs) impact 7% to 14% of all children in developed countries and are one of the leading causes of lifelong disability. Epigenetic modifications are poised at the interface between genes and environment and are predicted to reveal insight into the gene networks, cell types, and developmental timing of NDD etiology. Whole-genome bisulfite sequencing was used to examine DNA methylation in 49 human cortex samples from three different NDDs (autism spectrum disorder, Rett syndrome, and Dup15q syndrome) and matched controls. Integration of methylation differences across NDDs with relevant genomic and genetic datasets revealed differentially methylated regions (DMRs) unique to each type of NDD but with shared regulatory functions in neurons and microglia. DMRs were significantly enriched for known NDD genetic risk factors, including both common inherited and rare de novo variants. Weighted region co-methylation network analysis revealed a module related to NDD diagnosis and enriched for microglial regulatory regions. Together, these results demonstrate an epigenomic signature of NDDs in human cortex shared with known genetic and immune etiological risk. Epigenomic insights into cell types and gene regulatory regions will aid in defining therapeutic targets and early biomarkers at the interface of genetic and environmental NDD risk factors.

genomics

The first set of universal nuclear protein-coding loci markers for avian phylogenetic and population genetic studies

Multiple nuclear markers provide genetic polymorphism data for molecular systematics and population genetic studies. They are especially required for the coalescent-based analyses that can be used to accurately estimate species trees and infer population demographic histories. However, in avian evolutionary studies, these powerful coalescent-based methods are hindered by the lack of a sufficient number of markers. In this study, we designed PCR primers to amplify 136 nuclear protein-coding loci (NPCLs) by scanning the published Red Junglefowl (Gallus gallus) and Zebra Finch (Taeniopygia guttata) genomes. To test their utility, we amplified these loci in 41 bird species representing 23 Aves orders. The sixty-three best-performing NPCLs, based on high PCR success rates, were selected which had various mutation rates and were evenly distributed across 17 avian autosomal chromosomes and the Z chromosome. To test phylogenetic resolving power of these markers, we conducted a Neoavian phylogenies analysis using 63 concatenated NPCL markers derived from 48 whole genomes of birds. The resulting phylogenetic topology, to a large extent, is congruence with results resolved by previous whole genome data. To test the level of intraspecific polymorphism in these makers, we examined the genetic diversity in four populations of the Kentish Plover (Charadrius alexandrinus) at 17 of NPCL markers chosen at random. Our results showed that these NPCL markers exhibited a level of polymorphism comparable with mitochondrial loci. Therefore, this set of pan-avian nuclear protein-coding loci has great potential to facilitate studies in avian phylogenetics and population genetics.

evolutionary biology

Metabolomic consequences of genetic inhibition of PCSK9 compared with statin treatment

BackgroundBoth statins and PCSK9 inhibitors lower blood low-density lipoprotein cholesterol (LDL-C) levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these two lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial, and compared the results with the effects of genetic inhibition of PCSK9, acting as a naturally occurring trial.\n\nMethods228 circulating metabolic measures were quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5,359 individuals (2,659 on treatment) in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial at 6-months post-randomization. The corresponding metabolic measures were analyzed in eight population cohorts (N=72,185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors.\n\nResultsScaled to an equivalent lowering of LDL-C, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R2=0.88). Alterations in lipoprotein lipid composition and fatty acid balance were similar. However, discrepancies were observed for very-low-density lipoprotein (VLDL) lipid measures. For instance, genetic inhibition of PCSK9 showed weaker effects on lowering of VLDL-cholesterol compared with statin therapy (54% vs. 77% reduction, relative to the lowering effect on LDL-C; P=2 x 10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no robust effects on amino acids, ketones, and a marker of inflammation (GlycA); in contrast, statin treatment lowered GlycA levels.\n\nConclusionsGenetic inhibition of PCSK9 results in similar metabolic effects as statin therapy across a detailed lipid and metabolite profile. However, for the same lowering of LDL-C, PCSK9 inhibitors are predicted to be less efficacious than statins at lowering VLDL lipids, which could potentially translate into subtle differences in cardiovascular risk reduction.

epidemiology

Identifying the genetic basis of variation in cell behaviour in human iPS cell lines from healthy donors

Large cohorts of human iPSCs from healthy donors are potentially a powerful tool for investigating the relationship between genetic variants and cellular phenotypes. Here we integrate high content imaging, gene expression and DNA sequence datasets for over 100 human iPSC lines to identify the genetic basis of inter-individual variability in cell behaviour. By applying a dimensionality reduction approach, Probabilistic Estimation of Expression Residuals (PEER), we identified genes that correlated in expression with intrinsic (genetic) and extrinsic (ECM) factors. However, variation in mRNA levels could not account for outlier cell behaviour. Instead, we identified rare, deleterious SNVs in the coding sequence of genes involved in ECM adhesion that occurred in cell lines that were outliers for one or more phenotypes such as cell spreading. These also correlated with altered germ layer differentiation on micropatterned surfaces. Our study thus establishes a strategy for integrating genetic and cell biological measurements for high-throughput analysis.

cell biology

A genetic link between whole-plant water use efficiency and leaf carbon isotope composition in the C4 grass Setaria

Increasing whole plant water use efficiency (yield per transpiration; WUEplant) through plant breeding can benefit the sustainability of agriculture and improve crop yield under drought. To select for WUEplant, an efficient phenotyping method that reports on the genetic contribution of component traits such as transpiration efficiency (TEi; rate of CO2 assimilation per stomatal conductance) must be developed. Leaf carbon stable isotope composition ({delta}13Cleaf) has been proposed as a high-throughput proxy for TEi, and a negative correlation between {delta}13Cleaf and both WUEplant and TEi has previously been demonstrated in several C4 grass species. Therefore, the aim of the research presented here was to determine if the same loci control {delta}13Cleaf, WUEplant, and TEi under well-watered and water-limited conditions in a recombinant inbred line (RIL) population of closely related C4 grasses Setaria viridis and S. italica. Three quantitative trait loci (QTL) for {delta}13Cleaf were co-localized with transpiration, biomass, and a linear model of WUE. When WUEplant was calculated for allele classes based on the three QTL for {delta}13Cleaf, {delta}13Cleaf was negatively correlated with WUEplant as theory predicts when WUEplant is in part driven by differences in TEi. In any population, multiple traits can influence WUEplant; however, the analysis of {delta}13Cleaf in this RIL population demonstrates that there is genetic control of TEi that significantly contributes to WUEplant. Furthermore, this research suggests that {delta}13Cleaf can be used in marker-assisted breeding to select for TEi and as a tool to better understand the physiology and genetic architecture of TEi and WUEplant in C4 species.\n\nSignificance StatementOverextended water resources and drought are major agricultural problems worldwide. Therefore, selection for increased plant water use efficiency (WUEplant) in food and biofuel crop species is an important trait in plant breeding programs. Leaf carbon isotopic composition ({delta}13Cleaf) has potential as a rapid and effective high throughput phenotyping method for intrinsic transpiration efficiency (TEi), an important leaf-level component trait of WUEplant. Our research shows that {delta}13Cleaf and WUEplant share a common genetic architecture through their shared relationship with TEi. This suggests that {delta}13Cleaf can be used as a screen for TEi in marker-assisted plant breeding programs to improve crop drought resistance and decrease agricultural water consumption.

plant biology

TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data

Much of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of >3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with >200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high copy number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.

bioinformatics

Genetic variation/evolution and differential host responses resulting from in-patient adaptation of Mycobacterium avium

Mycobacterium avium (Mav) complex (MAC) are characterized as non-tuberculosis mycobacteria and are pathogenic mainly in immunocompromised individuals. MAC strains show a wide genetic variability, and there is growing evidence suggesting that genetic differences may contribute to a varied immune response that may impact on the infection outcome. The current study aimed to characterize the genomic changes within Mav isolates collected from single patients over time and test the host immune responses to these clinical isolates. Pulsed field gel electrophoresis and whole genome sequencing was performed on 40 MAC isolates isolated from 15 patients at the Department of Medical Microbiology at St. Olavs Hospital in Trondheim, Norway. Patients (4, 9 and 13) who contributed more than two isolates were selected for further analysis. These isolates exhibited extensive sequence variation in the form of single nucleotide polymorphisms (SNPs), suggesting that Mav accumulates mutations at high rates during persistent infections. Infection of murine macrophages and mice with sequential isolates from patients showed a tendency towards increased persistence and down-regulation of inflammatory cytokines by host-adapted Mav strains. The study revealed rapid genetic evolution of Mav in chronically infected patients accompanied with change in virulence properties of the sequential mycobacterial isolates.\n\nIMPORTANCEMAC are a group of opportunistic pathogens, consisting of Mav and M. intracellulare species. Mav is found ubiquitously in the environment. In Mav infected individuals, Mav has been known to persist for long periods of time, and anti-mycobacterial drugs are unable to effectively clear the infection. The continued presence of the bacteria, could be attributed to either a single persistent strain or reinfection with the same or different strain. We examined sequential isolates collected over time from Mav infected individuals and observed that most patients carried the same strain overtime and were not re infected. We observed high rates of mutation within the serial isolates, accompanied with changes in virulence properties. In the light of increase in incidence of MAC related infections, this study highlights the possibility that host adapted Mav undergo genetic modifications to cope with the host environment and thereby persisting longer.

immunology