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bioRxiv2016

Genetic correlations among brain-behavioral and immune-related phenotypes based on genome-wide association data.

Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies (GWASs) to determine if commonly varying single nucleotide polymorphisms (SNPs) are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (HESS) methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohns disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations amongst the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study.

Bioinformatics↗

bioRxiv2016

HOMINID: A framework for identifying associations between host genetic variation and microbiome composition

Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome composition data, identifies host SNPs that are correlated with microbial taxa abundances. Using simulated data we show that HOMINID has accuracy in identifying associated SNPs, and performs better compared to existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition, and can facilitate discovery of mechanisms controlling host-microbiome interactions.\n\nAvailability and implementationSoftware, code, tutorial, installation and setup details, and synthetic data are available in the project homepage: https://github.com/blekhmanlab/hominid.\n\nReal dataset used here is from Blekhman et al. (Blekhman et al. 2015); 16S rRNA gene sequence data and OTU tables are available on the HMP DACC website (www.hmpdacc.org), and host genetic data are deposited in dbGaP under project number phs000228.

genomics↗

bioRxiv2017

Improving prediction of compound function from chemical structure using chemical-genetic networks

The drug discovery process can be significantly improved through understanding how the structure of chemical compounds relates to their function. A common paradigm that has been used to filter and prioritize compounds is ligand-based virtual screening, where large libraries of compounds are queried for high structural similarity to a target molecule, with the assumption that structural similarity is predictive of similar biological activity. Although the chemical informatics community has already proposed a wide range of structure descriptors and similarity coefficients, a major challenge has been the lack of systematic and unbiased benchmarks for biological activity that covers a broad range of targets to definitively assess the performance of the alternative approaches.\n\nWe leveraged a large set of chemical-genetic interaction data from the yeast Saccharomyces cerevisiae that our labs have recently generated, covering more than 13,000 compounds from the RIKEN NPDepo and several NCI, NIH, and GlaxoSmithKline (GSK) compound collections. Supportive of the idea that chemical-genetic interaction data provide an unbiased proxy for biological functions, we found that many commonly used structural similarity measures were able to predict the compounds that exhibited similar chemical-genetic interaction profiles, although these measures did exhibit significant differences in performance. Using the chemical-genetic interaction profiles as a basis for our evaluation, we performed a systematic benchmarking of 10 different structure descriptors, each combined with 12 different similarity coefficients. We found that the All-Shortest Path (ASP) structure descriptor paired with the Braun-Blanquet similarity coefficient provided superior performance that was robust across several different compound collections.\n\nWe further describe a machine learning approach that improves the ability of the ASP metric to capture biological activity. We used the ASP fingerprints as input for several supervised machine learning models and the chemical-genetic interaction profiles as the standard for learning. We found that the predictive power of the ASP fingerprints (as well as several other descriptors) could be substantially improved by using support vector machines. For example, on held-out data, we measured a 5-fold improvement in the recall of biologically similar compounds at a precision of 50% based upon the ASP fingerprints. Our results generally suggest that using high-dimensional chemical-genetic data as a basis for refining chemical structure descriptors can be a powerful approach to improving prediction of biological function from structure.

systems biology↗

bioRxiv2017

Vast population genetic diversity underlies the treatment dynamics of ETV6-RUNX1 ALL

Ensemble-averaged genome profiling of diagnostic samples suggests that acute leukemias harbor few somatic genetic alterations. We used single-cell exome and error-corrected sequencing to survey the genetic diversity underlying ETV6-RUNX1 acute lymphoblastic leukemia (ALL) at high resolution. The survey uncovered a vast range of low-frequency genetic variants that were undetected in conventional bulk assays, including additional clone-specific \"driver\" RAS mutations. Single-cell exome sequencing revealed APOBEC mutagenesis to be important in disease initiation but not in progression and identified many more mutations per cell than previously found. Using this data, we created a branching model of ETV6-RUNX1 ALL development that recapitulates the genetic features of patients. Exposure of leukemic populations to chemotherapy selected for specific clones in a dose-dependent manner. Together, these data have important implications for understanding the development and treatment response of childhood leukemia, and they provide a framework for using population genetics to deeply interrogate cancer clonal evolution.\n\nOne-Sentence SummaryAPOBEC and replication-associated mutagenesis contribute to the development of ETV6-RUNX1 ALL, creating massive leukemic population genetic diversity that results in clonal differences in susceptibilities to chemotherapy.

cancer biology↗

bioRxiv2017

Effects of partial selfing on the equilibrium genetic variance, mutation load and inbreeding depression under stabilizing selection

The mating system of a species is expected to have important effects on its genetic diversity. In this paper, we explore the effects of partial selfing on the equilibrium genetic variance Vg, mutation load L and inbreeding depression{delta} under stabilizing selection acting on a arbitrary number n of quantitative traits coded by biallelic loci with additive effects. Overall, our model predicts a decrease in the equilibrium genetic variance with increasing selfing rates; however, the relationship between self-fertilization and the variables of interest depends on the strength of associations between loci, and three different regimes are observed. When the U/n ratio is low (where U is the total haploid mutation rate on selected traits) and effective recombination rates are sufficiently high, genetic associations between loci are negligible and the genetic variance, mutation load and inbreeding depression are well predicted by approximations based on single-locus models. For higher values of U/n and/or lower effective recombination, moderate genetic associations generated by epistasis tend to increase Vg, L and{delta} , this regime being well predicted by approximations including the effects of pairwise associations between loci. For yet higher values of U/n and/or lower effective recombination, a different regime is reached under which the maintenance of coadapted gene complexes reduces Vg, L and{delta} . Simulations indicate that the values of Vg, L and{delta} are little affected by assumptions regarding the number of possible alleles per locus.

evolutionary biology↗

bioRxiv2017

Integrating genomic resources for a threatened Caribbean coral (Orbicella faveolata) using a genetic linkage map developed from individual larval genotypes

Genomic methods are powerful tools for studying evolutionary responses to selection, but the application of these tools in non-model systems threatened by climate change has been limited by the availability of genomic resources in those systems. High-throughput DNA sequencing has enabled development of genome and transcriptome assemblies in non-model systems including reef-building corals, but the fragmented nature of early draft assemblies often obscures the relative positions of genes and genetic markers, and limits the functional interpretation of genomic studies in these systems. To address this limitation and improve genomic resources for the study of adaptation to ocean warming in corals, weve developed a genetic linkage map for the mountainous star coral, Orbicella faveolata. We analyzed genetic linkage among multilocus SNP genotypes to infer the relative positions of markers, transcripts, and genomic scaffolds in an integrated genomic map. To illustrate the utility of this resource, we tested for genetic associations with bleaching responses and fluorescence phenotypes, and estimated genome-wide patterns of population differentiation. Mapping the significant markers identified from these analyses in the integrated genomic resource identified hundreds of genes linked to significant markers, highlighting the utility of this resource for genomic studies of corals. The functional interpretations drawn from genomic studies are often limited by the availability of genomic resources linking genes to genetic markers. The resource developed in this study provides a framework for comparing genetic studies of O. faveolata across genotyping methods or references, and illustrates an approach for integrating genomic resources that may be broadly useful in other non-model systems.

genomics↗

bioRxiv2017

Partial restoration of mutational robustness after addition of genetic polymorphism and in the presence of sexual selection

The interaction between mutational (i.e. genetic) robustness, cryptic genetic variation and epistasis is currently under much debate, as is the question whether mutational robustness evolved under direct selection or as a by-product of environmental robustness. Here we report that mutational robustness was restored in a mutant line of the butterfly Bicyclus anynana after the spontaneous mutation, comet, appeared in a genetically polymorphic wild type population. The comet mutation modified two phenotypic traits known to be under sexual selection in this butterfly: the dorsal forewing eyespot, which is normally round, but became comet-shaped, and the androconia, the structures producing the male sex pheromone, which were reduced in size. The comet mutant line remained phenotypically stable for [~]7 seven years, but when outcrossed to the genetically polymorphic wild type population, the outcrossed comet line surprisingly recovered the wild type phenotype within 8 generations. This suggests that mutational robustness against the comet mutation was recovered in the comet outcrossed line by epistatic interactions with the genetic polymorphism originating from wild types. The extent of wild type phenotype recovery in the comet outcrossed line was trait- and developmental temperature-dependent, such that mutational robustness was partially recovered at high, but not at low developmental temperatures. We hypothesized that sexual selection through mate choice, which is sex-reversed between developmental temperatures in this butterfly, could produce mutational robustness at a high (but not at a low) temperature. Females are the choosy sex and exert stabilizing or directional selection on male secondary sexual wing traits but only at higher temperatures. Male mating success experiments under semi-natural conditions then revealed that males with the typical comet mutant phenotype suffered from lower mating success compared to wild type males, while mating success of comet males resembling wild types was partially restored. Altogether, we document the roles of cryptic genetic variation and epistasis in restoration of mutational robustness against a spontaneous mutation with known fitness effects, and we provide experimental evidence, for the first time to our knowledge, that sexual selection can produce mutational robustness.

evolutionary biology↗

bioRxiv2019

Loss of genetic diversity in wild fish populations reduces biomass stability over time.

Genetic diversity sustains species adaptation. However, it may also support key ecosystems functions and services that can be altered by the worldwide loss of genetic diversity. Here, using long-term wild fish data, we demonstrate that populations with high genetic diversity do not reach higher biomasses than populations with low genetic diversity. Nonetheless, populations with high genetic diversity have much more stable biomasses over recent decades than populations having suffered from genetic erosion, which has implications for the provision of ecosystem services and the risk of population extinction. Our results strengthen the importance of adopting prominent environmental policies to conserve this important biodiversity facet.

ecology↗

bioRxiv2020

Genetic diversity and evolution of Hantaan virus in China and its neighbors

BackgroudHantaan virus (HTNV), as one of the pathogenic hantaviruses of HFRS, has raised serious concerns in Eurasia. China and its neighbors, especially Russia and South Korea, are seriously suffered HTNV infections. Recent studies reported genetic diversity and phylogenetic features of HTNV in different parts of China, but the analyses from the holistic perspective are rare. Methodology and Principal FindingsTo better understand HTNV genetic diversity and dynamics, we analyzed all available complete sequences derived from the S and M segments with bio-informatic tools. Our study revealed 11 phylogroups and sequences showed obvious geographic clustering. We found 42 significant amino acid variants sites and 18 of them located in immune epitopes. Nine recombination events and seven reassortment isolates were deteced in our study. Sequences from Guizhou were highly genetic divergent, characterized by the emergence of multiple lineages, recombination and reassortment events. We found that HTNV probably emerged in Zhejiang about 1,000 years ago and the population size expanded from 1980s to 1990s. Bayesian stochastic search variable selection analysis revealed that Heilongjiang, Shaanxi and Guizhou played important roles in HTNV evolution and migration. Conclusions/SignificanceThese findings reveal the original and evolution features of HTNV which might assist in understanding Hantavirus epidemics and would be useful for disease prevention and control. Author summaryHemorrhagic Fever with Renal Syndrome (HFRS) and Hantavirus Pulmonary Syndrome (HPS) are endemic zoonotic infectious diseases caused by hantaviruses that belong to the Family Bunyaviridae. Hantaviruses have gained worldwide attention as etiological agents of emerging zoonotic diseases, with fatality rates ranging from <10% up to 60%. However, our knowledge about the emergence and evolution of HTNV is limited. To get more information about HTNV genetic diversity and phylogenetic features in holistic perspective, we investigated the genetic diversity and spatial distribution of HTNV using all available whole genomic sequences of S and M segments. We also gain insights into the genetic diversity and spatial-temporal dynamics of HTNV. These data can augment traditional approach to infectious disease surveillance and control.

evolutionary biology↗

bioRxiv2020

Genetic variants drive altered epigenetic regulation of endotoxin tolerance in BTBR macrophages

The BTBR T+Itpr3tf/J (BTBR) mouse has been used as a complex genetic model of Autism Spectrum Disorders (ASD). While the specific mechanisms underlying BTBR behavioral phenotypes are poorly understood, prior studies have implicated profound differences in innate immune system control of pro-inflammatory cytokines. Innate immune activation and elevated pro-inflammatory cytokines are also detected in blood of children with ASD. In this study, we examined how underlying BTBR genetic variants correspond to strain-specific changes in chromatin accessibility, resulting in a pro-inflammatory response specifically in BTBR bone marrow derived macrophages (BMDM). In response to repeated lipopolysaccharide (LPS) treatments, C57BL/6J (C57) BMDM exhibited intact endotoxin tolerance. In contrast, BTBR BMDM exhibited hyper-responsive expression of genes that were normally tolerized in C57. This failure in formation of endotoxin tolerance in BTBR was mirrored at the level of chromatin accessibility. Using ATAC-seq, we specifically identified promoter and enhancer regions with strain-specific differential chromatin accessibility both at baseline and in response to LPS. Regions with strain-specific differences in chromatin accessibility were significantly enriched for BTBR genetic variants, such that an average of 22% of the differential chromatin regions had at least one variant. Together, these results demonstrate that BTBR genetic variants contribute to altered chromatin responsiveness to endotoxin challenge and a failure in formation of tolerance, resulting in a hyper-responsive innate immunity in BTBR. These findings provide evidence for an interaction between complex genetic variants and differential epigenetic regulation of innate immune responses. Our findings also provide novel mechanistic insight into the complex genetic architecture and immune abnormalities observed in ASD.

molecular biology↗

bioRxiv2020

Ecological niche models as hypothesis generators of functional genetic differentiation and potential local adaptation in a Mediterranean alpine ecosystem

Geographically disparate populations within a species range may show important differences including variation in ecological, demographic, genetic and phenotypic characteristics. Based on the Center-Periphery Hypothesis, it is often assumed that environmental conditions are optimal in the geographic center of the range and stressful or suboptimal at the periphery, implying ecological marginality is concordant with geographic periphery. But this assumption has been challenged as geographical and ecological gradients are not necessarily concordant. The conservation value of populations inhabiting environmentally marginal areas is still under debate and is closely related with their evolutionary potential. Strong selective pressures caused by stressful conditions may generate novel adaptations in marginal areas, conferring these populations distinct evolutionary potential. But populations inhabiting marginal areas may also show reductions in neutral and adaptive genetic diversity via drift and inbreeding. In this work we explore the potential of ecological niche models (ENMs) to identify environmentally optimal and marginal areas, as well as the principal putative selective pressures likely to act. To do so, we built a carefully parameterized ENM of Silene ciliata, a dominant plant species of Mediterranean alpine habitats. Complementarily, we selected wild populations inhabiting contrasting environmental conditions and carried out common garden experiments to detect genetic differentiation among populations associated with functional traits. With the resulting information, we tested whether environmentally marginal populations defined by the ENM had genetically differentiated phenotypes that are potentially adaptive and, thus, of conservation value. We found genetically based phenotypic differentiation of phenological traits between populations inhabiting areas identified by the ENM as marginal and optimal, as well as between populations with different habitat suitability values. Results supported ENMs as powerful tools for determining environmental marginality and identifying selection pressures, and thus also as hypothesis generators for divergent selection. Furthermore, genetically based phenotypic differentiation found underlines the potential adaptive value of populations inhabiting marginal areas. The approach developed here provides a theoretically justified and practical way to study adaptive processes and provide insights about the conservation value of marginal populations.

evolutionary biology↗

bioRxiv2020

Genetic association of FMRP targets with psychiatric disorders

AO_SCPLOWBSTRACTC_SCPLOWGenes encoding the mRNA targets of Fragile X mental retardation protein (FMRP) are enriched for genetic association with psychiatric disorders. However, many FMRP targets possess functions that are themselves genetically associated with psychiatric disorders, including synaptic transmission and plasticity, making it unclear whether the genetic risk is truly related to binding by FMRP or is alternatively mediated by the sampling of genes better characterised by another trait or functional annotation. Using published common variant, rare coding variant and copy number variant data, we examined the relationship between FMRP binding and genetic association with schizophrenia, major depressive disorder and bipolar disorder. We then explored the partitioning of genetic association between overrepresented functional categories. High-confidence targets of FMRP were enriched for common schizophrenia risk alleles, as well as rare loss-of-function and de novo nonsynonymous variants in cases. Similarly, through common variation, FMRP targets were associated with major depressive disorder, and we present novel evidence of association with bipolar disorder. These relationships could not be explained by membership of other functional annotations known to be associated with psychiatric disorders, including those related to synaptic structure and function. This study reinforces the evidence that targeting by FMRP captures a subpopulation of genes enriched for genetic association with a range of psychiatric disorders, across traditional diagnostic boundaries.

neuroscience↗

bioRxiv2020

Polyploidization enhancing genetic recombination of the ancestral diploid genome in the evolution of hexaploid wheat

Allopolyploidy increases its evolutionary potential by fixing heterosis and the advantage of gene redundancy. Allelic combinations generated from genetic recombination potentially provide many variations to the selection pools for evolution. May there be any relationship between allopolyploidization and genetic recombination? To study the impact of polyploidy on genetic recombination, we selected wheat as a model and simulated its evolution pathway of allopolyploidy by developing synthetic hexaploid wheat. The change of homologous chromosome recombination were investigated on their diploid DD and tetraploid AABB genomes after their allohexaploidization, respectively. The genetic recombination of the ancestral diploid genome of Aegilops tauschii was enhanced significantly more than 2 folds after their hexaploidization. Hexaploidization enhancing genetic recombination of the ancestral diploid D genome was firstly reported to be a new way to increase evolutionary potential of wheat, which is beneficial for wheat to conquer their narrow origination of D genome, quickly spread and make it a major crop of the world. Finally, re-synthetizing hexaploid wheat using diverse Ae. tauschii species with tetraploid wheat can be considered as a pleiotropic strategy to speed adaptive evolution of bread wheat in breeding processes by increasing both gene allele types and genetic recombination variations.

evolutionary biology↗

bioRxiv2020

Genetic structure, function and evolution of capsule biosynthesis loci in Vibrio parahaemolyticus

Capsule-forming extracellular polysaccharides are crucial to bacterial host colonization, invasion, immune evasion and ultimately pathogenicity. Due to warming ocean waters and human encroachment of coastal ecosystems, Vibrio parahaemolyticus has emerged as a globally important food-borne enteropathogen implicated in acute gastroenteritis, wound infections, and septic shock. Conventionally, the antigenic properties of lipopolysaccharide (LPS, O antigen) and capsular polysaccharide (CPS, K antigen) have provided a basis for serotyping V. parahaemolyticus, while disclosure of genetic elements encoding 13 O-serogroups have allowed molecular serotyping methods to be developed. However, the genetic structure of CPS loci for 71 K-serogroups has remained unidentified, limiting progress in understanding its roles in V. parahaemolyticus pathophysiology. In this study, we identified and characterized the genetic structure and their evolutionary relationship of CPS loci of 40 K-serogroups through whole genome sequencing of 443 V. parahaemolyticus strains. We found a distinct pattern of CPS gene cluster across different K-serogroups, and expanded its new right-border by identifying glpX as a key gene conserved across all serotypes. A total of 217 genes involved in CPS biosynthesis were annotated. Functional contents and genetic structure of the 40 K-serogroups were analyzed. Based on inferences from species trees and gene trees, we proposed an evolution model of the CPS gene clusters of 40 K-serogroups. Horizontal gene transfer by recombination from other Vibrio species, gene duplication and nonsense mutations are likely to play instrumental roles in the evolution of CPS in V. parahaemolyticus. It is the first time, to the best of our knowledge, that a large-scale of CPS gene clusters of different K-serogroups in V. parahaemolyticus have been identified and characterized in evolutionary contexts. This work should help advance understanding on the variation of CPS in V. parahaemolyticus, and provide a framework for developing diagnostically relevant serotyping methods. Author summaryDue to warming ocean waters and human encroachment of coastal ecosystems, Vibrio parahaemolyticus has emerged as a globally important food-borne enteropathogen. However, the genetic structure of CPS loci for 71 K-serogroups V. parahaemolyticus have remained unidentified, limiting progress in understanding its roles in V. parahaemolyticus pathophysiology. In this study, we identified and characterized the genetic structure of CPS loci of 40 K-serogroups through whole genome sequencing of 443 V. parahaemolyticus strains. We expanded and identified its new right-border by identifying glpX as a key gene conserved across all serotypes. We proposed an evolution model of the CPS gene clusters of 40 K-serogroups. We also found horizontal gene transfer by recombination from other Vibrio species, gene duplication and nonsense mutations are likely to play instrumental roles in the evolution of CPS in V. parahaemolyticus. It is the first time, to the best of our knowledge, that a large-scale of CPS loci of different K-serogroups in V. parahaemolyticus have been identified and characterized in evolutionary contexts. This work should help advance understanding on the variation of CPS in V. parahaemolyticus, and provide a framework for developing diagnostically relevant serotyping methods.

microbiology↗

bioRxiv2020

Can genetic polymorphisms predict response variability to anodal transcranial direct current stimulation of the primary motor cortex?

Genetic mediation of cortical plasticity and the role genetic variants play in previously observed response variability to transcranial direct current stimulation (tDCS) have become important issues in the tDCS literature in recent years. This study investigated whether inter-individual variability to tDCS was in-part genetically mediated. In sixty-one healthy males, anodal-tDCS (a-tDCS) and sham-tDCS were administered to the primary motor cortex at 1mA for 10-minutes via 6x4cm active and 7x5cm return electrodes. Twenty-five single-pulse transcranial magnetic stimulation (TMS) motor evoked potentials (MEP) were recorded to represent corticospinal excitability (CSE). Twenty-five paired-pulse MEPs were recorded with 3ms inter-stimulus interval (ISI) to assess intracortical inhibition (ICI) via short-interval intracranial inhibition (SICI) and 10ms ISI for intracortical facilitation (ICF). Saliva samples tested for specific genetic polymorphisms in genes encoding for excitatory and inhibitory neuroreceptors. Individuals were sub-grouped based on a pre-determined threshold and via statistical cluster analysis. Two distinct subgroups were identified, increases in CSE following a-tDCS (i.e. Responders) and no increase or even reductions in CSE (i.e. Non-responders). No changes in ICI or ICF were reported. No relationships were reported between genetic polymorphisms in excitatory receptor genes and a-tDCS responders. An association was reported between a-tDCS responders and GABRA3 gene polymorphisms encoding for GABA-A receptors suggesting potential relationships between GABA-A receptor variations and capacity to undergo tDCS-induced cortical plasticity. In the largest tDCS study of its kind, this study presents an important step forward in determining the contribution genetic factors play in previously observed inter-individual variability to tDCS.

neuroscience↗

bioRxiv2020

Genetic similarity and facial cues for kin recognition in humans

Kin recognition is essential to the evolution of human cooperation, social organization, and altruistic behavior. However, the genetic underpinnings of kin recognition have been largely understudied. Facial resemblance is an important relatedness cue for humans and more closely related individuals are generally thought to share greater facial similarity. To evaluate the relationship between perceived self-resemblance and genetic similarity among biologically related and unrelated females, we administered facial self-recognition surveys to twenty-three sets of related females and genotyped three different genetic systems, human leukocyte antigens (HLA), neutral nuclear microsatellites and mitochondrial haplogroups, for each individual. Using these data, we examined the relationship between visual kin recognition and genetic similarity. We found that pairs of individuals identified as visually more similar had greater HLA allelic sharing when compared to less facially similar participants. We did not find the same relationship for microsatellite and mitochondrial similarity, suggesting that HLA allelic similarity increases the probability of perceived self-resemblance in humans while other genetic markers do not. Our results demonstrate that some genetic markers, such as HLA-DRB, may have significant influence on phenotype and that large scale surveys of HLA and facial feature morphology will yield valuable insight into the evolutionary biology of genotype-phenotype relationships and kin recognition.

evolutionary biology↗

bioRxiv2020

Jchain-driven cre enables specific genetic manipulation and timestamping of plasma cell in their niche.

Plasma cells (PC)s are essential for protection from infection, and at the origin of incurable cancers. Current studies do not circumvent limitations of removing PCs from their microenvironment and confound formation and maintenance. This is in part due to the lack of tools to perform specific genetic manipulation in vivo. Also, studies of PC population dynamics have mostly relied on the use of nucleotide analog incorporation that does not label quiescent cells, a property of most PCs. Here we characterize in detail a genetic tool (JchaincreERT2) that permits first-ever specific genetic manipulation in PC in vivo, across immunoglobulin isotypes. Using this tool we found that PC numbers remained constant over-time and that PC decay was compensated by the emergence of new cells, supporting an homeostatic turnover of the population. The JchaincreERT2 genetic tool paves the way for in-depth mechanistic understanding of PC biology and pathology in vivo, in their microenvironment. HighlightsJchain expression occurs in most plasma cells across immunoglobulin isotypes JchaincreERT2 mediated genetic manipulation is effective only in plasma cells Genetic timestamping of plasma cells reveals homeostatic regulation

immunology↗

bioRxiv2020

Ecology and population genetics of the parasitoid Phobocampe confusa (Hymenoptera: Ichneumonidae) in relation to its hosts, Aglais species (Lepidoptera: Numphalidae).

The biology of parasitoids in natural ecosystems remain very poorly studied, while they are key species for their functioning. Here we focused on Phobocampe confusa, a vanessines specialist, responsible for high mortality rates in very emblematic butterfly species in Europe (genus Aglais). We studied its ecology and genetic structure in connection with those of its host butterflies in Sweden. To this aim, we gathered data from 428 P. confusa individuals reared from 6094 butterfly larvae (of A. urticae, A. io and in two occasions of Araschnia levana) collected over two years (2017 and 2018) and 19 sites distributed along a 500 km latitudinal gradient. We found that P. confusa is widely distributed along the latitudinal gradient. Its distribution is constrained over time by the phenology of its hosts. The large variation in climatic conditions between sampling years explains the decrease in phenological overlap between P. confusa and its hosts in 2018 and the 33.5% decrease in the number of butterfly larvae infected. At least in this study, P. confusa seems to favour A. urticae as host: while it parasitized nests of A. urticae and A. io equally, the proportion of larvae is significantly higher for A. urticae. At the landscape scale, P. confusa is almost exclusively found in vegetated open land and near deciduous forests, whereas artificial habitats are negatively correlated with the likelihood of a nest to be parasitized. The genetic analyses on 89 adult P. confusa and 87 adult A. urticae using COI and AFLP markers reveal a low genetic diversity in P. confusa and a lack of population genetic structure in both species, at the scale of our sampling. Further genetic studies using high-resolution genomics tools will be required to better understand the population genetic structure of P. confusa, its biotic interactions with its hosts, and ultimately the stability and the functioning of natural ecosystems.Competing Interest StatementThe authors have declared no competing interest.View Full Text

zoology↗