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Results for “Genetics”

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bioRxiv2019

Machine Learning based histology phenotyping to investigate epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the relationship between adipocyte area and obesity-related traits, and identify genetic factors associated with adipocyte cell size. To perform the first large-scale study of automatic adipocyte phenotyping using both histological and genetic data, we developed a deep learning-based method, the Adipocyte U-Net, to rapidly derive area estimates from histology images. We validate our method using three state-of-the-art approaches; CellProfiler, Adiposoft and floating adipocytes fractions, all run blindly on two external cohorts. We observe high concordance between our method and the state-of-the-art approaches (Adipocyte U-net vs. CellProfiler: R2visceral= 0.94, P < 2.2 x 10-16, R2subcutaneous= 0.91, P < 2.2 x 10-16), and faster run times (10,000 images: 6mins vs 3.5hrs). We applied the Adipocyte U-Net to 4 cohorts with histology, genetic, and phenotypic data (total N = 820). After meta-analysis, we found that adipocyte area positively correlated with body mass index (BMI) (Psubq = 8.13 x 10-69, {beta}subq = 0.45; Pvisc= 2.5 x 10-55, {beta}visc= 0.49; average R2 across cohorts = 0.49) and that adipocytes in subcutaneous depots are larger than their visceral counterparts (Pmeta= 9.8 x 10-7). Lastly, we performed the largest GWAS and subsequent meta-analysis of adipocyte area and intra-individual adipocyte variation (N = 820). Despite having twice the number of samples than any similar study, we found no genome-wide significant associations, suggesting that larger sample sizes and a homogenous collection of adipose tissue are likely needed to identify robust genetic associations.

genomics↗

bioRxiv2019

Rescue of Tomato spotted wilt tospovirus entirely from cDNA clones, establishment of the first reverse genetics system for a segmented (-)RNA plant virus

The group of negative strand RNA viruses (NSVs) includes not only dangerous pathogens of medical importance but also serious plant pathogens of agronomical importance. Tomato spotted wilt tospovirus (TSWV) is one of those plant NSVs that cause severe diseases on agronomic crops and pose major threats to global food security. Its negative-strand segmented RNA genome has, however, always posed a major obstacle to molecular genetic manipulation. In this study, we report the complete recovery of infectious TSWV entirely from cDNA clones, the first reverse genetics (RG) system for a segmented plant NSV. First, a replication and transcription competent mini-genome replication system was established based on 35S-driven constructs of the S(-)-genomic (g) or S(+)-antigenomic (ag) RNA template, flanked by a 5 Hammerhead and 3 Ribozyme sequence of Hepatitis Delta virus, a nucleocapsid (N) protein gene and codon-optimized viral RNA dependent RNA polymerase (RdRp) gene. Next, a movement competent mini-genome replication system was developed based on M(-)-gRNA, which was able to complement cell-to-cell and systemic movement of reconstituted ribonucleoprotein complexes (RNPs) of S RNA replicon. After further optimization, infectious TSWV and derivatives carrying eGFP reporters were successfully rescued in planta via simultaneous expression of full-length cDNA constructs coding for S(+)-agRNA, M(-)-gRNA and L(+)-agRNA. Viral rescue occurred in the additional presence of various viral suppressors of RNAi, but TSWV NSs interfered with the rescue of genomic RNA. The establishment of a RG system for TSWV now allows detailed molecular genetic analysis of all aspects of tospovirus life cycle and their pathogenicity.\n\nSignificanceFor many different animal-infecting segmented negative-strand viruses (NSVs), a reverse genetics system has been established that allows the generation of mutant viruses to study disease pathology and the role of cis- and trans-acting elements in the virus life cycle. In contrast to the relative ease to establish RG systems for animal-infecting NSVs, establishment of such system for the plant-infecting NSVs with a segmented RNA genome so far has not been successful. Here we report the first reverse genetics system for a segmented plant NSV, the Tomato spotted wilt tospovirus, a virus with a tripartite RNA genome. The establishment of this RG system now provides us with a new and powerful platform to study their disease pathology during a natural infection.

microbiology↗

bioRxiv2019

Genetic research at the intersection of gender identity, sexual orientation, and mental health: community attitudes and recommendations for researchers

Biological sex is an important factor in mental health, and a non-binary view of how variation in sex and gender influence mental health represents a new research frontier that may yield new insights. The recent acceleration of research into sexual orientation, gender identity, and mental health has generally been conducted without sufficient understanding of the opinions of sexual and gender minorities (SGM) toward this research. We surveyed 768 individuals, with an enrichment of LGBTQ+ stakeholders, for their opinions regarding genetic research of SGM and mental health. We found that the key predictors of attitudes toward genetic research specifically on SGM are 1) general attitudes toward genetic and mental health research 2) tolerance of SGM and associated behaviors 3) non-cisgender stakeholder status and 4) age of the respondent. Non-heterosexual stakeholder status was significantly associated with increased willingness to participate in genetic research if a biological basis for gender identity were discovered. We also found that non-stakeholders with a low tolerance for SGM indicated their SGM views would be positively updated if science showed a biological basis for their behaviors and identities. These findings represent an important first step in understanding and engaging the LGBTQ+ stakeholder community in the context of genetic research.

scientific communication and education↗

bioRxiv2019

Partners in health? Investigating social genetic effects for married and cohabiting couples.

Social contagion research suggests that health behaviors (BMI, smoking, drinking, etc.) spread through social networks, including dyadic ties such as between married/cohabiting partners. However, separating contagion from assortative mating ( like seeks like) and shared environmental factors remains notoriously difficult in observational studies. It is not possible to obtain exogenous variation in long-term partnerships ( random mating), but genetic approaches can offer a novel way to examine partner similarity and the role of social contagion. This paper explores possible social genetic effects among partners, i.e., effects of the partners genes on ones own behavior. We use the longitudinal Health and Retirement Study with data on health behavior and genomic data for both ego and his/her partner to examine social genetic effects for BMI, drinking, and smoking behavior. For each outcome, we find support for social genetic effects. Americans of European descent were more overweight if they had partners with higher polygenic scores for BMI net of their own polygenic score. Similar findings were found for the number of drinks per week and cigarettes per day. Longitudinal analyses that conditioned on past health behavior of both spouses confirmed these findings. We further explored whether susceptibility to the partners influence differed between men and women, but did not find consistent differences across outcomes. Findings are further discussed in the light of ramifications of social genetic effects for the social and biological sciences.

genomics↗

bioRxiv2019

Genetically encoded nanostructures enable acoustic manipulation of engineered cells

The ability to mechanically manipulate and control the spatial arrangement of biological materials is a critical capability in biomedicine and synthetic biology. Ultrasound has the ability to manipulate objects with high spatial and temporal precision via acoustic radiation force, but has not been used to directly control biomolecules or genetically defined cells. Here, we show that gas vesicles (GVs), a unique class of genetically encoded gas-filled protein nanostructures, can be directly manipulated and patterned by ultrasound and enable acoustic control of genetically engineered GV-expressing cells. Due to their differential density and compressibility relative to water, GVs experience sufficient acoustic radiation force to allow these biomolecules to be moved with acoustic standing waves, as demonstrated within microfluidic devices. Engineered variants of GVs differing in their mechanical properties enable multiplexed actuation and act as sensors of acoustic pressure. Furthermore, when expressed inside genetically engineered bacterial cells, GVs enable these cells to be selectively manipulated with sound waves, allowing patterning, focal trapping and translation with acoustic fields. This work establishes the first genetically encoded nanomaterial compatible with acoustic manipulation, enabling molecular and cellular control in a broad range of contexts.

bioengineering↗

bioRxiv2019

Phenotypic plasticity, but not genetic adaptation, underlies seasonal variation in the cold hardening response of Drosophila melanogaster

In temperate regions, an organisms ability to rapidly adapt to seasonally varying environments is essential for its survival. In response to seasonal changes in selection pressure caused by variation in temperature, humidity, and food availability, some organisms exhibit plastic changes in phenotype. In other cases, seasonal variation in selection pressure can rapidly increase the frequency of genotypes that offer survival or reproductive advantages under the current conditions. Little is known about the relative influences of plastic and genetic changes in short lived organisms experiencing seasonal environmental fluctuations. Cold hardening is a seasonally relevant plastic response in which exposure to cool, but nonlethal, temperatures significantly increases the organisms ability to later survive at freezing temperatures. In the present study, we demonstrate seasonal variation in cold hardening in Drosophila melanogaster and test the extent to which plasticity and adaptive tracking underlie that seasonal variation. We measured the cold hardening response of flies from outdoor mesocosms over the summer, fall, and winter. We bred outdoor mesocosm-caught flies for two generations in the lab and matched each outdoor cohort to an indoor control cohort of similar genetic background. We measured the cold hardening response of indoor and field-caught flies and their laboratory-reared F1 and F2 progeny to determine the roles of seasonal environmental plasticity, parental effects, and genetic changes on cold hardening. We also tested the relationship between cold hardening and other factors, including age, developmental density, food substrate, presence of antimicrobials, and supplementation with live yeast. We found strong plastic responses to a variety of field- and lab-based environmental effects, but no evidence of seasonally varying parental or genetic effects on cold hardening. We therefore conclude that seasonal variation in the cold hardening response results from environmental influences and not genetic changes.

evolutionary biology↗

bioRxiv2019

Kin recognition and genetic variation for competitive ability in the annual legume Medicago minima

Knowing which mechanisms drive the outcome of intraspecific interactions is highly relevant for understanding diversity maintenance. Plant species that exhibit strong genetic substructure over small spatial scales may be exposed to frequent interactions with closely related individuals. Predictions of how genetic similarity may drive the outcome of intraspecific interactions are based on two contrasting theories: the resource partitioning hypothesis and kin selection theory. The first predicts that competition will be stronger among closely related conspecific (i.e. kin) because similar genotypes have similar resource requirements. The second predicts instead that competition will be reduced among kin, in order to maximize the inclusive fitness. Although efforts have been made to reconcile these two theories as non-mutually exclusive, the outcomes of intraspecific interaction studies are frequently interpreted as the results of either one or the other. We experimentally tested the hypothesis that intraspecific interactions may be driven by both genetic variation for competitive ability and reduced competition among kin. We used an annual legume, Medicago minima, to conduct two greenhouse experiments testing changes in root behaviour, above-ground growth and biomass in response to neighbour identity. We found evidence of both genetic variation for competitive ability and reduced competition among kin in some genotypes. Reduced competitive growth towards kin was found in the most competitive genotypes, suggesting that kin avoidance and competitive ability were simultaneously affecting plant behaviour and growth. With presence of both kin competition avoidance and variation for competitive ability, the outcome of intraspecific interactions will strongly depend on the local spatial genetic substructure. This is highly relevant to predict how intraspecific competition affect diversity maintenance.

ecology↗

bioRxiv2019

Cryptic genetic variation underpins rapid adaptation to ocean acidification

Global climate change has intensified the need to assess the capacity for natural populations to adapt to abrupt shifts in the environment. Reductions in seawater pH constitute a conspicuous stressor associated with increasing atmospheric carbon dioxide that is affecting ecosystems throughout the worlds oceans. Here, we quantify the phenotypic and genetic modifications associated with rapid adaptation to reduced seawater pH in the marine mussel, Mytilus galloprovincialis. We reared a genetically diverse larval population in ambient and extreme low pH conditions (pHT 8.1 and 7.4) and tracked changes in the larval size and allele frequency distributions through settlement. Additionally, we separated larvae by size to link a fitness-related trait to its underlying genetic background in each treatment. Both phenotypic and genetic data show that M. galloprovincialis can evolve in response to a decrease in seawater pH. This process is polygenic and characterized by genotype-environment interactions, suggesting the role of cryptic genetic variation in adaptation to future climate change. Holistically, this work provides insight into the processes underpinning rapid evolution, and demonstrates the importance of maintaining standing variation within natural populations to bolster species adaptive capacity as global change progresses.

evolutionary biology↗

bioRxiv2019

Bottleneck Size-Dependent Changes in the Genetic Diversity and Specific Growth Rate of a Rotavirus A Strain

RNA viruses form a dynamic distribution of mutant swarm (termed \"quasispecies\") due to the accumulation of mutations in the viral genome. The genetic diversity of a viral population is affected by several factors, including a bottleneck effect. Human-to-human transmission ex-emplifies a bottleneck effect in that only part of a viral population can reach the next susceptible hosts. In the present study, the rhesus rotavirus (RRV) strain of Rotavirus A was serially passaged five times at a multiplicity of infection (MOI) of 0.1 or 0.001 in duplicate (the 1st and 2nd lineages), and three phenotypes (infectious titer, cell binding ability and specific growth rate) were used to evaluate the impact of a bottleneck effect on the RRV population. The specific growth rate values of lineages passaged under the stronger bottleneck (MOI of 0.001) were higher after five passages. The nucleotide diversity also increased, which indicated that the mutant swarms of the lineages under the stronger bottleneck effect were expanded through the serial passages. The random distribution of synonymous and non-synonymous substitutions on rotaviral genome segments indicated that almost all mutations were selectively neutral. Simple simulations revealed that the presence of minor mutants could influence the specific growth rate of a population in a mutant frequency-dependent manner. These results indicate that a stronger bottleneck effect can create more sequence spaces for minor mutants originally existing in a hidden layer of mutant swarm.\n\nIMPORTANCEIn this study, we investigated a bottleneck effect on an RRV population, which may drastically impact a viral population structure. RRV populations were serially passaged under two levels of a bottleneck effect, which exemplified a human-to-human transmission. As a result, the genetic diversity and specific growth rate of RRV populations increased under the stronger bottleneck effect, which implied that a bottleneck could create a new sequence space in a population for minor mutants originally existing in a hidden layer of a mutant swarm of the double-stranded RNA virus. The results of this study suggest that the genetic drift caused by a bottleneck in a human-to-human transmission explains the random appearance of new genetic lineages causing viral outbreaks, which can be expected by the molecular epidemiology using next generation sequencing in which the viral genetic diversity within a viral population is investigated.

microbiology↗

bioRxiv2019

Resolving genetic linkage reveals patterns of selection in HIV-1 evolution

Identifying the genetic drivers of adaptation is a necessary step in understanding the dynamics of rapidly evolving pathogens and cancer. However, signals of selection are obscured by the complex, stochastic nature of evolution. Pervasive effects of genetic linkage, including genetic hitchhiking and clonal interference between beneficial mutants, challenge our ability to distinguish the selective effect of individual mutations. Here we describe a method to infer selection from genetic time series data that systematically resolves the confounding effects of genetic linkage. We applied our method to investigate patterns of selection in intrahost human immunodeficiency virus (HIV)-1 evolution, including a case in an individual who develops broadly neutralizing antibodies (bnAbs). Most variants that arise are observed to have negligible effects on inferred selection at other sites, but a small minority of highly influential variants have strong and far-reaching effects. In particular, we found that accounting for linkage is crucial for estimating selection due to clonal interference between escape mutants and other variants that sweep rapidly through the population. We observed only modest selection for antibody escape, in contrast with strong selection for escape from CD8+ T cell responses. Weak selection for escape from antibody responses may facilitate bnAb development by diversifying the viral population. Our results provide a quantitative description of the evolution of HIV-1 in response to host immunity, including selection on the viral population that accompanies bnAb development. More broadly, our analysis argues for the importance of resolving linkage effects in studies of natural selection.

evolutionary biology↗

bioRxiv2019

Machine learning based detection of genetic and drug class variant impact on functionally conserved protein binding dynamics

The application of statistical methods to comparatively framed questions about protein dynamics can potentially enable investigations of biomolecular function beyond the current sequence and structural methods in bioinformatics. However, chaotic behavior in single protein trajectories requires statistical inference be obtained from large ensembles of molecular dynamic (MD) simulations representing the comparative functional states of a given protein. Meaningful interpretation of such a complex form of big data poses serious challenges to users of MD. Here, we announce DROIDS v3.0, a molecular dynamic (MD) method + software package for comparative protein dynamics, incorporating many new features including maxDemon v1.0, a multi-method machine learning application that trains on large ensemble comparisons of concerted protein motions in opposing functional states and deploys learned classifications of these states onto newly generated protein dynamic simulations. Local canonical correlations in learning patterns generated from self-similar MD runs are used to identify regions of functionally conserved protein dynamics. Subsequent impacts of genetic and drug class variants on conserved dynamics can also be analyzed by deploying the classifiers on variant MD runs and quantifying how often these altered protein systems display the opposing functional states. Here, we present several case studies of complex changes in functional protein dynamics caused by temperature, genetic mutation, and binding interaction with nucleic acids and small molecules. We studied the impact of genetic variation on functionally conserved protein dynamics in ubiquitin and TATA binding protein and demonstrate that our learning algorithm can properly identify regions of conserved dynamics. We also report impacts to dynamics that correspond well with predicted disruptive effects of a variety of genetic mutations. In addition, we studied the impact of drug class variation on the ATP binding region of Hsp90, similarly identifying conserved dynamics and impacts that rank accordingly with how closely various Hsp90 inhibitors mimic natural ATP binding.\n\nStatement of significanceWe propose a statistical method as well as offer a user-friendly graphical interfaced software pipeline for comparing simulations of the complex motions (i.e. dynamics) of proteins in different functional states. We also provide both method and software to apply artificial intelligence (i.e. machine learning methods) that enable the computer to recognize complex functional differences in protein dynamics on new simulations and report them to the user. This method can identify dynamics important for protein function, as well as to quantify how the motions of molecular variants differ from these important functional dynamic states. For the first time, this method of analysis allows the impacts of different genetic backgrounds or drug classes to be examined within the context of functional motions of the specific protein system under investigation.

biophysics↗

bioRxiv2019

Establishment of a Reverse Genetics System for Influenza D Virus

Influenza D virus (IDV) was initially isolated in the USA in 2011. IDV is distributed worldwide and is one of the causative agents of bovine respiratory disease complex (BRDC), which exhibits high morbidity and mortality in feedlot cattle. Molecular mechanisms of IDV pathogenicity are still unknown. Reverse genetics systems are vital tools not only for studying the biology of viruses, but also for use in applications such as recombinant vaccine viruses. Here, we report the establishment of a plasmid-based reverse genetics system for IDV. We first verified that the 3'-terminal nucleotide of each 7-segmented genomic RNA contained uracil in contrary to the previous report, and were then able to successfully generate recombinant IDV by co-transfecting 7 plasmids containing these genomic RNAs along with 4 plasmids expressing polymerase proteins and NP into HRT-18G cells. The recombinant virus had a growth deficit compared to the wild-type virus, and we determined the reason for this growth difference by examining the genomic RNA content of the viral particles. We found that recombinant virus incorporated an unbalanced ratio of viral RNA segments into particles as compared to the wild-type virus, and thus we adjusted the amount of each plasmid used in transfection to obtain recombinant virus with the same replicative capacity as wild-type virus. Our work here in establishing a reverse genetics system for IDV will have a broad range of applications, including uses in studies focused on better understanding IDV replication and pathogenicity as well as those contributing to the development of BRDC countermeasures.\n\nIMPORTANCEBovine respiratory disease complex (BRDC) exhibits high mortality and morbidity in cattle, causing economic losses worldwide. Influenza D virus (IDV) is considered to be a causative agent of BRDC. Here, we developed a reverse genetics system that allows for the generation of IDV from cloned cDNAs, and the introduction of mutations into the IDV genome. This reverse genetics system will become a powerful tool for use in studies related to understanding the molecular mechanisms of viral replication and pathogenicity, and will also lead to the development of new countermeasures against BRDC.

microbiology↗

bioRxiv2019

Genetic variation in herbivore resistance within a strawberry crop wild relative (Fragaria vesca L.)

To decrease the dependency on chemical pesticides, the resistance of cultivated strawberry to pests needs to be increased. While genetic resources within domesticated varieties are limited, wild genotypes are predicted to show high heritable variation in useful resistance traits. We collected 86 wild accessions of Fragaria vesca L. from central Sweden and screened this germplasm for antibiosis (pest survival and performance) and antixenosis (pest preference) traits active against the strawberry leaf beetle (Galerucella tenella L.). First, extensive common garden experiments were used to study antibiosis traits in the sampled plant genotypes. Heritable genetic variation among plant genotypes was found for several antibiosis traits. Second, controlled cafeteria experiments were used to test for plant genetic variation in antixenosis traits. The leaf beetles avoided egg laying on plant genotypes possessing high antibiosis. This indicates a high degree of concordance between antibiosis and antixenosis, and that the beetles egg-laying behaviour optimizes the fitness of their offspring. The existence of high genetic variation in key resistance traits suggests that wild woodland strawberry contains untapped resources that are sought to reduce pesticide-dependence in cultivated strawberry. Given that only a very small portion of the species distribution area was sampled, even higher variation may be expected at the continental scale. As a whole, the genetic resources identified in this study serve to strengthen the position of woodland strawberry as a key crop wild relative.

plant biology↗

bioRxiv2019

Scalable probabilistic PCA for large-scale genetic variation data

Principal component analysis (PCA) is a key tool for understanding population structure and controlling for population stratification in genome-wide association studies (GWAS). With the advent of large-scale datasets of genetic variation, there is a need for methods that can compute principal components (PCs) with scalable computational and memory requirements. We present ProPCA, a highly scalable method based on a probabilistic generative model, which computes the top PCs on genetic variation data efficiently. We applied ProPCA to compute the top five PCs on genotype data from the UK Biobank, consisting of 488,363 individuals and 146,671 SNPs, in less than thirty minutes. Leveraging the population structure inferred by ProPCA within the White British individuals in the UK Biobank, we scanned for SNPs that are not well-explained by the PCs to identify several novel genome-wide signals of recent putative selection including missense mutations in RPGRIP1L and TLR4.\n\nAuthor SummaryPrincipal component analysis is a commonly used technique for understanding population structure and genetic variation. With the advent of large-scale datasets that contain the genetic information of hundreds of thousands of individuals, there is a need for methods that can compute principal components (PCs) with scalable computational and memory requirements. In this study, we present ProPCA, a highly scalable statistical method to compute genetic PCs efficiently. We systematically evaluate the accuracy and robustness of our method on large-scale simulated data and apply it to the UK Biobank. Leveraging the population structure inferred by ProPCA within the White British individuals in the UK Biobank, we identify several novel signals of putative recent selection.

bioinformatics↗

bioRxiv2019

Feedback loops involving AMPK, ERK and TFEB in matrix detachment leads to non-genetic heterogeneity

Cancer cells metastasize by evading apoptosis induced due to the detachment from the extracellular matrix. Deciphering the adaptive strategies employed by cancer cells in matrix-deprived condition can help design novel therapeutic strategies to tackle metastasis. Here, we provide evidence for non-genetic heterogeneity in matrix-detached cells enabled by feedback loop among AMPK, ERK and TFEB that determines autophagy maturation and cell survival. The subpopulation of matrix-detached cells with pAMPKlow/pERKhigh/TFEBlow state show autophagy maturation arrest and elevated cell death. Conversely, pAMPKhigh/pERKlow/ TFEBhigh cells show high autophagy maturation and better cell survival. We show that AMPK inhibits ERK activity in suspension; ERK negatively regulates TFEB which promotes autophagy maturation and re-enforces AMPK. Inhibition of ERK promotes autophagy maturation, cell survival and metastasis in vivo, while AMPK inhibition (and TFEB depletion) renders the population homogeneous by depleting the pAMPKhigh/pERKlow/TFEBhigh subpopulation, driving detachment-induced death. Such non-genetic heterogeneity is further deciphered by mathematical modelling and RNA-sequencing data of circulating tumor cells (CTCs) isolated from breast cancer patients. Altogether, our work unravels a contextual feedback loop involving two kinases and a transcription factor that helps a subpopulation to evade cell death in matrix-deprived condition. Disrupting such feedback loops may offer improved therapeutic efficacy and a novel approach to constrain metastasis. Significance of the StudyAttachment to the extracellular matrix is pivotal for the growth and survival of normal epithelial cells. In contrast, cancer cells acquest the ability to survive matrix-deprivation and cause cancer spread, or metastasis, which is a leading cause of cancer-related deaths. Non-genetic heterogeneity within cancer cell populations is increasingly being recognized as a major cause of treatment failure. However, the implications of such heterogeneity in the survival of matrix-detached cancer cells remain poorly understood. In this study, we demonstrate feedback loops involving kinases and transcription factor to maintain non-genetic heterogeneous population, where population harbouring pAMPKhigh/pERKlow/TFEBhigh status shows survival advantage. Targeting such feedback loops that generate non-genetic heterogeneity can open newer therapeutic means to restrict cancer spread.

cancer biology↗

bioRxiv2019

Comparative genomics unravels mechanisms of genetic adaptation for the catabolism of the phenylurea herbicide linuron in Variovorax

Biodegradation of the phenylurea herbicide linuron appears a specialization within a specific clade of the Variovorax genus. The linuron catabolic ability is likely acquired by horizontal gene transfer but the mechanisms involved are not known. The full genome sequences of six linuron degrading Variovorax strains isolated from geographically distant locations were analyzed to acquire insight in the mechanisms of genetic adaptation towards linuron metabolism in Variovorax. Whole genome sequence analysis confirmed the phylogenetic position of the linuron degraders in a separate clade within Variovorax and indicated their unlikely origin from a common ancestral linuron degrader. The linuron degraders differentiated from non-degraders by the presence of multiple plasmids of 20 to 839 kb, including plasmids of unknown plasmid groups. The linuron catabolic gene clusters showed (i) high conservation and synteny and (ii) strain-dependent distribution among the different plasmids. All were bordered by IS1071 elements forming composite transposon structures appointing IS1071 as key for catabolic gene recruitment. Most of the strain carried at least one broad host range plasmid that might have been a second instrument for catabolic gene acquisition. We conclude that clade 1Variovorax strains, despite their different geographical origin, made use of a limited genetic repertoire to acquire linuron biodegradation.\n\nImportanceThe genus Variovorax and especially a clade of strains that phylogenetically separates from the majority of Variovorax species, appears to be a specialist in the biodegradation of the phenyl urea herbicide linuron. Horizontal gene transfer (HGT) likely played an essential role in the genetic adaptation of those strain to acquire the linuron catabolic genotype. However, we do not know the genetic repertoire involved in this adaptation both regarding catabolic gene functions as well as gene functions that promote HGT neither do we know how this varies between the different strains. These questions are addressed in this paper by analyzing the full genome sequences of six linuron degrading Variovorax strains. This knowledge is important for understanding the mechanisms that steer world-wide genetic adaptation in a particular species and this for a particular phenotypic trait as linuron biodegradation.

microbiology↗

bioRxiv2019

Genetic Portrait of North-West Indian Population based on X Chromosome Alu Insertion Markers

Alu insertion elements represent the largest family of Short Interspersed Nuclear Elements (SINEs) in the human genome. Polymorphic Alu elements are stable and conservative markers that can potentially be applied in studying human origin and relationships as they are identical by descent and known for lack of insertion in ancestral state. In this study, 10 Alu insertions of X chromosome were utilized to tabulate allele frequency distributions and compute parameters of forensic relevance in the 379 unrelated healthy individuals belonging to four different ethnic groups (Brahmin, Khatri, Jat Sikh and Scheduled Caste) of North-West India. Furthermore, the DA and FST values of pairwise interpopulation differentiations, multidimensional scaling and Bayesian structure clustering analysis were also computed to probe the genetic relationships between present studied populations and with other 21 reference populations. Six X-Alu insertions were observed to be polymorphic in all the populations, whereas the others appeared as monomorphic in at least one studied population. The insertion allele frequencies were in the range of 0.15 at Ya5DP3 to 0.9888 at Ya5DP77. Most polymorphic Alu elements showed moderate to low genetic diversity. The maximum value of power of exclusion (PE) was 0.1645 at Ya5NBC37 marker, whereas the minimum was 0.0001 at Ya5DP4 locus, implying the significance of X chromosome Alu elements in forensic genetic investigations. Genetic relationships agree with a geographical pattern of differentiation among populations. The results of present study establish that X chromosome Alu elements comprise a reliable set of genetic markers useful to describe human population relationships and structure.

evolutionary biology↗

bioRxiv2019

Annual replication is essential in evaluating the response of the soil microbiome to the genetic modification of maize in different biogeographical regions

The importance of geographic location and annual variation on the detection of differences in the rhizomicrobiome caused by the genetic modification of maize (Bt-maize, event MON810) was evaluated at experimental field sites across Europe including Sweden, Denmark, Slovakia and Spain. DNA of the rhizomicrobiome was collected at the maize flowering stage in three consecutive years and analyzed for the abundance and diversity of PCR-amplified structural genes of Bacteria, Archaea and Fungi, and functional genes for bacterial nitrite reductases (nirS, nirK). The nirK genes were always more abundant than nirS. Maize MON810 did not significantly alter the abundance of any microbial genetic marker, except for sporadically detected differences at individual sites and years. In contrast, annual variation between sites was often significant and variable depending on the targeted markers. Distinct, site-specific microbial communities were detected but the sites in Denmark and Sweden were similar to each other. A significant effect of the genetic modification of the plant on the community structure in the rhizosphere was detected among the nirK denitrifiers at the Slovakian site in only one year. However, most nirK sequences with opposite response were from the same or related source organisms suggesting that the transient differences in community structure did not translate to the functional level. Our results show a lack of effect of the genetic modification of maize on the rhizosphere microbiome that would be stable and consistent over multiple years. This demonstrates the importance of considering annual variability in assessing environmental effects of genetically modified crops.

microbiology↗