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Polygenic barriers to gene flow: the role of dominance, haploid selection and heterogeneous genetic architectures

We consider how the genetic architecture underlying locally adaptive traits determines the strength of a barrier to gene flow in a mainland-island model. Assuming a general life cycle, we derive an expression for the effective migration rate when local adaptation is due to a polygenic trait under directional selection on the island, allowing for arbitrary fitness and dominance effects across loci. We show how the effective migration rate can be combined with classical single-locus diffusion theory to accurately predict multilocus differentiation between the mainland and island at migration-selection-drift equilibrium and determine the migration rate beyond which local adaptation collapses, while accounting for genetic drift and weak linkage. Using our efficient numerical tools, we then present a detailed study of the effects of dominance on barriers to gene flow, showing that when total selection is sufficiently strong, more recessive local adaptation generates stronger barriers to gene flow. We show that details of the haplodiplontic life cycle can be captured using a set of effective parameters, and consider how the relative strength of selection in the two phases affects barriers to gene flow. We then study how heterogeneous genetic architectures of local adaptation affect barriers to gene flow, characterizing adaptive differentiation at migration-selection balance for different distributions of fitness effects. We find that a more heterogeneous genetic architecture generally yields a stronger genome-wide barrier to gene flow and that the detailed genetic architecture underlying locally adaptive traits can have an important effect on observable differentiation when divergence is not too large. Lastly, we study the limits of our approach as loci become more tightly linked, showing that our predictions remain accurate over a large biologically relevant domain.

evolutionary biology↗

Association of leaf spectral variation with functional genetic variants

The application of in-field and aerial spectroscopy to assess functional and phylogenetic variation in plants has led to novel ecological insights and supports global assessments of plant biodiversity. Understanding how plant genetic variation influences reflectance spectra will help harness this potential for biodiversity monitoring and improve understanding of why plants differ in functional responses to environmental change. Here, we use a well-resolved genetic mapping population derived from Multi-parent Advanced Generation Inter-cross (MAGIC) lines of Nicotiana attenuata to associate genetic differences with differences in leaf spectra between plants in a field experiment in their natural environment. We analyzed the leaf reflectance spectra using a hand-held spectroradiometer (350-2500 nm) on 616 fully genotyped plants of N. attenuata grown in a randomized block design. We tested three approaches to conducting Genome-Wide Association Studies on spectral variants. We introduce a new Hierarchical Spectral Clustering with Parallel Analysis (HSC-PA) method. This method efficiently captured the variation in our high-dimensional dataset and allowed us to discover a novel association, between a locus on chromosome 1 and the 734-1143 nm spectral range, spanning the red-edge and near-infrared regions that are sensitive to leaf structure and photosynthetic activity. This locus contains a candidate gene annotated as carbonic anhydrase, an enzyme involved in CO2 hydration and regulation of photosynthetic efficiency, suggesting a physiological link between variation in leaf optical properties and carbon assimilation. In contrast, an approach treating single wavelengths as phenotypes identified the same associations as HSC-PA, but without the statistical power to pinpoint significant associations. An index-based approach, which reduces complex spectra to a few dimensionless variables, detected two significant associations for ARDSI_Cw (a water-content-related index) with loci on chromosome 1 near genes annotated as a Zeta toxin domain-containing protein, and an Exocyst subunit Exo70 family protein. While these findings are biologically plausible, they represent a very narrow subset of the spectral variation captured by HSC-PA. The HSC-PA approach supports a comprehensive understanding of the genetic determinants of leaf spectral variation which is data-driven but human-interpretable, and lays a robust foundation for future research in linking plant genetics with biodiversity monitoring, large-scale ecological assessment and remote-sensing applications.

ecology↗

Distribution theories for genetic line of least resistance and evolvability measures

Quantitative genetic theory on multivariate character evolution predicts that a populations response to directional selection tends to happen around the major axis of the genetic covariance matrix G--the so-called genetic line of least resistance. Inferences on the genetic constraints in this sense have traditionally been made by measuring the angle of deviation of evolutionary trajectories from the major axis, or more recently by calculating the amount of genetic variance--the Hansen-Houle evolvability--available along the trajectories. However, there have not been clear practical guidelines on how these quantities can be interpreted, especially in a high-dimensional space. This study summarizes pertinent distribution theories for relevant quantities, pointing out that they can be written as ratios of quadratic forms in evolutionary trajectory vectors by taking G as a parameter. For example, a beta distribution with appropriate parameters can be used as a null distribution for squared cosine of the angle of deviation from a major axis or subspace. More general cases can be handled with the probability distribution of ratios of quadratic forms in normal variables. Apart from its use in hypothesis-testing, this latter approach could potentially be used as a heuristic tool for looking into various selection scenarios like directional and/or correlated selection as parameterized with mean and covariance of selection gradients.

evolutionary biology↗

High genetic diversification in a symbiotic marine annelid is driven by microgeography and glaciation

Marine invertebrates with limited dispersal abilities exhibit high levels of genetic divergence among populations. However, the spatial extent of genetic differentiation in these species remains poorly understood because identifying natural barriers to gene flow can be challenging in the marine environment. In this study, we investigated the population genetic structure of the interstitial annelid Olavius algarvensis, a species that lays eggs in its immediate surroundings and does not have an active dispersal phase. We analyzed the mitochondrial and nuclear genome sequences of hundreds to thousands of individuals from eleven sites in the Mediterranean, spanning microgeographic scales of < 5 km to macrogeographic scales of 800 km. Comparisons of single nucleotide polymorphisms (SNPs) in mitochondrial genomes revealed a complex history of introgression events, with as many as six mitochondrial lineages co-occurring in individuals from the same site. In contrast, SNP analyses of nuclear genomes revealed clear genetic differentiation at micro- and macrographic scales, characterised by a significant isolation by distance pattern (IBD). IBD patterns further indicated the presence of a historical physical barrier to gene flow on the east coast of the island of Elba corresponding to the historical shoreline around Elba during the Last Glacial Maximum in the Late Pleistocene, and highlighting the influence of geological forces in shaping population genetic structuring in the species today. Overall, our results provide strong empirical evidence for the high genomic diversification across spatial scales in marine interstitial fauna.

evolutionary biology↗

Epigenetic context predicts gene expression variation and reproductive traits across genetically identical individuals

In recent decades, genome-wide association studies (GWAS) have been the major approach to understand the biological basis of individual differences in traits and diseases. However, GWAS approaches have limited predictive power to explain individual differences, particularly for complex traits and diseases in which environmental factors play a substantial role in their etiology. Indeed, individual differences persist even in genetically identical individuals, although fully separating genetic and environmental causation is difficult in most organisms. To understand the basis of individual differences in the absence of genetic differences, we measured two quantitative reproductive traits in 180 genetically identical young adult Caenorhabditis elegans roundworms in a shared environment and performed single-individual transcriptomics on each worm. We identified hundreds of genes for which expression variation was strongly associated with reproductive traits, some of which depended on individuals historical environments and some of which was random. Multiple small sets of genes together were highly predictive of reproductive traits, explaining on average over half and over a quarter of variation in the two traits. We manipulated mRNA levels of predictive genes to identify a set of causal genes, demonstrating the utility of this approach for both prediction and understanding underlying biology. Finally, we found that the chromatin environment of predictive genes was enriched for H3K27 trimethylation, suggesting that gene expression variation may be driven in part by chromatin structure. Together, this work shows that individual, non-genetic differences in gene expression are both highly predictive and causal in shaping reproductive traits.

genomics↗

Detecting time-varying genetic effects in Alzheimer's disease using a longitudinal GWAS model

BackgroundThe development and progression of Alzheimers disease (AD) is a complex process that can change over time, during which genetic influences on phenotypes may also fluctuate. Incorporating longitudinal phenotypes in genome wide association studies (GWAS) could help unmask genetic loci with time-varying effects. In this study, we incorporated a varying coefficient test in a longitudinal GWAS model to identify single nucleotide polymorphisms (SNPs) that may have time- or age-dependent effects in AD. MethodsGenotype data from 1,877 participants in the Alzheimers Neuroimaging Data Initiative (ADNI) were imputed using the Haplotype Reference Consortium (HRC) panel, resulting in 9,573,130 SNPs. Subjects longitudinal impairment status at each visit was considered as a binary and clinical phenotype. Participants composite standardized uptake value ratio (SUVR) derived from each longitudinal amyloid PET scan was considered as a continuous and biological phenotype. The retrospective varying coefficient mixed model association test (RVMMAT) was used in longitudinal GWAS to detect time-varying genetic effects on the impairment status and SUVR measures. Post-hoc analyses were performed on genome-wide significant SNPs, including 1) pathway analyses; 2) age-stratified genotypic comparisons and regression analyses; and 3) replication analyses using data from the National Alzheimers Coordinating Center (NACC). ResultsOur model identified 244 genome-wide significant SNPs that revealed time-varying genetic effects on the clinical impairment status in AD; among which, 12 SNPs on chromosome 19 were successfully replicated using data from NACC. Post-hoc age-stratified analyses indicated that for most of these 244 SNPs, the maximum genotypic effect on impairment status occurred between 70 to 80 years old, and then declined with age. Our model further identified 73 genome-wide significant SNPs associated with the temporal variation of amyloid accumulation. For these SNPs, an increasing genotypic effect on PET-SUVR was observed as participants age increased. Functional pathway analyses on significant SNPs for both phenotypes highlighted the involvement and disruption of immune responses- and neuroinflammation-related pathways in AD. ConclusionWe demonstrate that longitudinal GWAS models with time-varying coefficients can boost the statistical power in AD-GWAS. In addition, our analyses uncovered potential time-varying genetic variants on repeated measurements of clinical and biological phenotypes in AD.

neuroscience↗

Small but significant genetic differentiation among populations of Phyllachora maydis in the midwestern United States revealed by microsatellite (SSR) markers.

Phyllachora maydis Maubl, the causal pathogen of tar spot of corn (Zea mays L.), has emerged recently in the United States and Canada. Studies related to its genetic diversity and population structure are limited and are necessary to improve our understanding of this pathogens biology, ecology, epidemiology, and evolutionary potential within this region. This study developed and used 13 microsatellites (SSR markers) to assess the genetic population structure, diversity, gene flow and reproductive mode of 181 P. maydis samples across five states in the Midwest U.S. The polymorphic information content (PIC) of loci ranged from 0.32 to 0.72 per locus, indicating their high utility for assessing the dynamics of P. maydis populations. Analysis of molecular variance (AMOVA) detected a significantly low, but statistically significant genetic differentiation (FST = 0.15) among populations, where 85% of the variance resided within populations. P. maydis populations were highly diverse (He = 0.55), with moderate gene flow (Nm = 2.80), and showed evidence of sexual recombination ([r]d; p = > 0.001). Structure analysis showed the samples were not geographically structured but rather grouped into two genetic clusters (k =2) of severe genetic admixture suggesting possible long-distance dispersal of aerial spores or infected corn materials among the five Midwest states. Both principal coordinate analysis (PCoA) and discriminate analysis of principal component (DAPC) supported the STRUCTURE analysis of the two clusters. These 13 highly polymorphic molecular markers could be used for future investigations of this pathogens population dynamics within the U.S., and possibly populations outside.

pathology↗

Intragenomic conflicts with plasmids and chromosomal mobile genetic elements drive the evolution of natural transformation within species

Natural transformation is the only mechanism of genetic exchange controlled by the recipient bacteria. We quantified its rates in 1282 strains of the human pathogens Legionella pneumophila (Lp) and Acinetobacter baumannii (Ab) and found that transformation rates evolve by large quick changes as a jump process across six orders of magnitude. Close to half of the strains are non-transformable in standard conditions. Transitions to non-transformability were frequent and recent, suggesting that they are deleterious and subsequently purged by natural selection. Accordingly, we find that transformation decreases genetic linkage in both species, which often accelerates adaptation. Intragenomic conflicts with chromosomal mobile genetic elements (MGEs) and plasmids could explain these transitions and a GWAS confirmed systematic negative associations between transformation and MGEs: plasmids and other conjugative elements in Lp, prophages in Ab, and transposable elements in both. In accordance with the modulation of transformation rates by genetic conflicts, transformable strains have fewer MGEs. Defense systems against the latter are associated with lower transformation except the adaptive CRISPR-Cas systems which show the inverse trend. The two species have different lifestyles and gene repertoires, but they exhibit very similar trends in terms of variation of transformation rates and its determinants, suggesting that genetic conflicts could drive the evolution of natural transformation in many bacteria.

genomics↗

A shift in the host web occupancy of dew-drop spiders associated with genetic divergence in the Southwest Pacific

AimWe assessed the population genetic structure of the kleptoparasitic spider Argyrodes bonadea across the Southwestern Pacific islands. Our focus is on assessing the impact of overseas distances and, in particular, the Kerama gap, as potential drivers of genetic differentiation. We found that the spider kleptoparasites switch to a specific host species is associated with significant genetic variation at fine scales, whereas the same species adoption of a generalist host strategy has likely facilitated its broad dispersal, colonization, and recent range expansion across the southwestern Pacific, and is associated with a lack of geographically- structured genetic variation in these latter, subsequently-colonized landmasses. LocationSouthwestern Pacific Islands TaxonArgyrodes bonadea MethodsWe used mitochondrial Cytochrome Oxidase 1 (CO1) gene sequences, and Restriction Site-associated DNA Sequencing (RAD-seq) for our analyses. ResultsTwo strongly supported lineages, an Amami-Okinawa Lineage (AOL) and an Austral-Asia Lineage (AAL) correspond to two separate clades, roughly divided by the Kerama Gap, in phylogenetic trees estimated here. However, species delimitation led to the interpretation of only a single species present. The AOL exhibits complex, geographically-structured host web spider species specificity, wherein the Amami population utilizes Cyrtophora, but AOL samples in Okinawa associates exclusively with Nephila--and yet all broadly distributed AAL populations show no evidence of host web spider species specificity. Main conclusionThe population boundary between AOL and AAL likely results from local adaptation to novel hosts--instead of isolation by the Kerama Gap--following long-distance dispersal and range expansion. Our results suggest kleptoparasitic spiders have the capacity to overcome permanent deep-sea barriers and colonize distant landmasses. Whereas peripheral populations (AOL) demonstrate the capacity for specialization to a single host, which may have contributed to genetic differentiation and isolation, the broadly-distributed AAL persists and has successfully expanded its geographical range as a host generalist, which may contribute to ongoing gene flow inferred in this study.

evolutionary biology↗

Functional genetic characterization of stress tolerance and biofilm formation in Nakaseomyces glabrata via a novel CRISPR activation system

The overexpression of genes frequently arises in Nakaseomyces (formerly Candida) glabrata via gain-of-function mutations, gene duplication or aneuploidies, with important consequences on pathogenesis traits and antifungal drug resistance. This highlights the need to develop specific genetic tools to mimic and study genetic amplification in this important fungal pathogen. Here, we report the development, validation, and applications of the first CRISPR activation (CRISPRa) system in N. glabrata for targeted genetic overexpression. Using this system, we demonstrate the ability of CRISPRa to drive high levels of gene expression in N. glabrata, and further assess optimal guide RNA targeting for robust overexpression. We demonstrate the applications of CRISPRa to overexpress genes involved in fungal pathogenesis and drug resistance, and detect corresponding phenotypic alterations in these key traits, including the characterization of novel phenotypes. Finally, we capture strain variation using our CRISPRa system in two commonly used N. glabrata genetic backgrounds. Together, this tool will expand our capacity for functional genetic overexpression in this pathogen, with numerous possibilities for future applications.

microbiology↗

Diverse Genetic Contexts of HicA Toxin Domains Propose a Role in Anti-Phage Defense

Toxin - antitoxin (TA) modules are prevalent in prokaryotic genomes, often in substantial numbers. For instance, the Mycobacterium tuberculosis genome alone harbors close to 100 TA modules, half of which belong to a singular type. Traditionally ascribed multiple biological roles, recent insights challenge these notions and instead indicate a predominant function in phage defense. TAs are often located within Defense Islands, genomic regions that encode various defense systems. The analysis of genes within Defense Islands have unveiled a wide array of systems, including TAs that serve in anti-phage defence. Prokaryotic cells are equipped with anti-phage Viperins that, analogous to their mammalian counterparts, inhibit viral RNA transcription. Additionally, bacterial Structural Maintenance of Chromosome (SMC) proteins combat plasmid intrusion by recognizing foreign DNA signatures. This study undertakes a comprehensive bioinformatics analysis of genetic elements encoding the HicA double-stranded RNA-binding domain, complemented by protein structure modeling. The HicA toxin domains are found in at least 14 distinct contexts and thus exhibit a remarkable genetic diversity. Traditional bicistronic TA operons represent eight of these contexts, while four are characterized by monocistronic operons encoding fused HicA domains. Two contexts involve hicA adjacent to genes that encode bacterial Viperins. Notably, genes encoding RelE toxins are also adjacent to Viperin genes in some instances. This configuration hints at a synergistic enhancement of Viperin-mediated anti-phage action by HicA and RelE toxins. The discovery of a HicA domain merged with an SMC domain is compelling, prompting further investigation into its potential roles. ImportanceProkaryotic organisms harbor a multitude of Toxin - Antitoxin (TA) systems, which have long puzzled scientists as "genes in search for a function". Recent scientific advancement have shed light on a primary role of TAs as anti-phage defense mechanisms. To gain an overview of TAs it is important to analyze their genetic contexts that can give hints on function and guide future experimental inquiries. This manuscript describes a thorough bioinformatics examination of genes encoding the HicA toxin domain, revealing its presence in no fewer than 14 unique genetic arrangements. Some configurations notably align with anti-phage activities, underscoring potential roles in microbial immunity. These insights robustly reinforce the hypothesis that HicA toxins are integral components of the prokaryotic anti-phage defense repertoire. The elucidation of these genetic contexts not only advances our understanding of TAs but also contributes to a paradigm shift in how we perceive their functionality within the microbial world.

bioinformatics↗

Extreme in Every Way: Exceedingly Low Genetic Diversity in Snow Leopards Due to Persistently Small Population Size

Snow leopards (Panthera uncia) serve as an umbrella species whose conservation benefits their high-elevation Asian habitat. Their numbers are believed to be in decline due to numerous Anthropogenic threats; however, their conservation is hindered by numerous knowledge gaps. They are the least studied genetically of all big cat species with more to learn regarding their population structure, historical population size, and current levels of genetic diversity. Here, we use whole-genome sequencing data for 41 snow leopards (37 newly sequenced) to offer new insights into these unresolved questions. Among our samples, we find evidence of a primary genetic divide between the northern and southern part of the range around the Dzungarian Basin, as previously identified, and a secondary divide south of Kyrgyzstan around the Taklamakan Desert. Most noteworthy, we find that snow leopards have the lowest genetic diversity of any big cat species, due to a persistently small population size (relative to other big cat species) throughout their evolutionary history rather than recent inbreeding. Without a large population size or ample standing genetic variation to help buffer them from any forthcoming Anthropogenic challenges, snow leopard persistence may be more tenuous than currently appreciated.

evolutionary biology↗

Genetic modification strategies for electroporation and CRISPR-Cas-based technologies in the non-competent Gram-negative bacterium Acinetobacter sp. Tol 5

Environmental isolates are promising candidates for new chassis of synthetic biology because of their inherent conversion capabilities and resilience to environmental stresses; however, many remain genetically intractable and unamenable to established genetic tools tailored for model bacteria. Acinetobacter sp. Tol 5 possesses intriguing properties for use in synthetic biology applications. However, genetic manipulation via electroporation is hindered by its low transformation efficiency. This study demonstrated the genetic refinement of the Tol 5 strain, achieving efficient transformation via electroporation. We deleted two genes encoding restriction enzymes. The resulting mutant strain not only exhibited marked efficiency of electrotransformation but also proved receptive to both in vitro and in vivo DNA assembly technologies, thereby facilitating the construction of recombinant DNA. In addition, we successfully adapted a CRISPR-Cas9-based base-editing platform developed for other Acinetobacter species. Our genetic modification strategy allows for the domestication of non-model bacteria, streamlining their utilization in synthetic biology applications.

synthetic biology↗

Uncovering the genetic architecture and evolutionary roots of androgenetic alopecia in African men

Androgenetic alopecia is a highly heritable trait. However, much of our understanding about the genetics of male pattern baldness comes from individuals of European descent. Here, we examined a novel dataset comprising 2,136 men from Ghana, Nigeria, Senegal, and South Africa that were genotyped using a custom array. We first tested how genetic predictions of baldness generalize from Europe to Africa, finding that polygenic scores from European GWAS yielded AUC statistics that ranged from 0.513 to 0.546, indicating that genetic predictions of baldness in African populations performed notably worse than in European populations. Subsequently, we conducted the first African GWAS of androgenetic alopecia, focusing on self-reported baldness patterns at age 45. After correcting for present age, population structure, and study site, we identified 266 moderately significant associations, 51 of which were independent (p-value < 10-5, r2 < 0.2). Most baldness associations were autosomal, and the X chromosomes does not appear to have a large impact on baldness in African men. Finally, we examined the evolutionary causes of continental differences in genetic architecture. Although Neanderthal alleles have previously been associated with skin and hair phenotypes, we did not find evidence that European-ascertained baldness hits were enriched for signatures of ancient introgression. Most loci that are associated with androgenetic alopecia are evolving neutrally. However, multiple baldness-associated SNPs near the EDA2R and AR genes have large allele frequency differences between continents. Collectively, our findings illustrate how evolutionary history contributes to the limited portability of genetic predictions across ancestries.

genomics↗

CellDemux: coherent genetic demultiplexing in single-cell and single-nuclei experiments.

Multiplexed single-cell experiment designs are superior in terms of reduced batch effects, increased cost-effectiveness, throughput and statistical power. However, current computational strategies using genetics to demultiplex single-cell (sc) libraries are limited when applied to single-nuclei (sn) sequencing data (e.g., snATAC-seq and snMultiome). Here, we present CellDemux: a computational framework for genetic demultiplexing within and across data modalities, including single-cell, single-nuclei and paired snMultiome measurements. CellDemux uses a consensus approach, leveraging modality-specific tools to robustly identify non-empty oil droplets and singlets, which are subsequently demultiplexed to donors. Notable, CellDemux demonstrates good performance in demultiplexing snMultiome data and is generalizable to single modalities, i.e. snATAC-seq and sc/snRNA-seq libraries. We benchmark CellDemux on 187 genetically multiplexed libraries from 800 samples (scRNA-seq, snATAC-seq, CITE-seq and snMultiome), confidently identifying and assigning cells to 88% of donors. In paired snMultiome libraries, CellDemux achieves consistent demultiplexing across data modalities. Moreover, analysis of 38 snATAC libraries from 149 samples shows that CellDemux retains more genetically demultiplexed nuclei for downstream analyses compared to existing methods. In summary, CellDemux is a modular and robust framework that deconvolves donors from genetically multiplexed single-cell and single-nuclei RNA/ATAC/Multiome libraries.

genomics↗

The unseen invaders: tracking phylogeographic dynamics and genetic diversity of cryptic Pomacea canaliculata and P. maculata (Golden Apple Snails) across Taiwan

The cryptic invasion of golden apple snails (Pomacea canaliculata and P. maculata) in Taiwan has caused significant ecological and economical damage over last few decades, however, their management remains difficult due to inadequate taxonomic identification, complex phylogeny and limited population genetic information. We aim to understand the current distribution, putative population of origin, genetic diversity and potential path of cryptic invasion of Pomacea canaliculata and P. maculata across Taiwan to aid in improved mitigation approaches. The present investigation conducted a nationwide survey with 254 samples collected from 41 locations from 14 counties or cities across Taiwan. We identified P. canaliculata and P. maculata based on mitochondrial COI and compared their genetic diversity across Taiwan, as well as other introduced and native countries (based on publicly available COI data) to understand the possible paths of invasion in Taiwan. Based on mitochondrial COI barcoding, sympatric and heterogeneous distributions of invasive P. canaliculata and P. maculata were noted. Our haplotype analysis and mismatch distribution suggested multiple introductions of P. canaliculata in Taiwan was likely originated directly from Argentina, whereas P. maculata was probably introduced from a single, or a few, introduction event(s) from Argentina and Brazil. Our population genetic data further demonstrated a higher haplotype and genetic diversity for P. canaliculata and P. maculata in Taiwan compared to other introduced regions. Based on our current understanding, the establishment of P. canaliculata and P. maculata is alarming and widespread beyond geopolitical borders, requiring a concerted and expedited national and international invasive species mitigation program.

ecology↗

Agriculturally developed areas reduce genetic connectivity for a keystone neotropical ungulate

Modified landscapes can restrict the movement of organisms, leading to isolation and reduced population viability, particularly for species with extensive home ranges and long-distance travel, such as white-lipped peccaries (WLPs, Tayassu pecari). Previous studies have indicated that forested areas favor WLP herd movements, but the impact of the non-forested areas on their genetic connectivity is unknown. In this study, we used land cover, the Brazilian Roads Map, and population genetic data to investigate the impact of non-forested matrices on WLPs genetic connectivity in the Pantanal floodplain and surrounding Cerrado plateau of central-west Brazil. We compared isolation-by-distance (IBD), isolation-by-barrier, and isolation-by-resistance models and tested 39 hypotheses within a modeling framework. Finally, we identified the optimal areas for ecological corridors based on the most effective landscape model. Barrier and landscape resistance were more strongly correlated with genetic relatedness than the IBD model. The model that received the most robust support considered only forest as habitat. All other classes formed a matrix that impeded gene flow, including agriculture, grassland, savannah, and paved and unpaved roads. WLP herds living in landscapes with reduced forest cover are more vulnerable to the effects of genetic isolation. To maintain gene flow, it is essential to establish connections between habitats throughout the landscape. Conservation programs should prioritize strategies that strengthen connections between habitats, including facilitating wildlife road-crossing structures and creating/restoring ecological corridors to link isolated habitat fragments.

ecology↗

Pangenomic landscapes shape the genetic circuit performance in a Stutzerimonas biodesign toolkit

Engineering identical genetic circuits into different species typically results in large differences in performance due to the unique cellular environmental context of each host, a phenomenon known as the "chassis-effect". A better understanding of how genomic and physiological contexts underpin the chassis-effect will greatly improve biodesign strategies across diverse microorganisms. Here, we combined a pangenomics-based gene expression analysis with quantitative measurements of performance from an engineered genetic inverter device to uncover how genome structure and function relates to the observed chassis-effect across six closely related Stutzerimonas hosts. Our results reveal that genome architecture underpins divergent responses between our chosen non-model bacterial hosts to engineered genetic circuits. Specifically, differential expression of the core genome, gene clusters shared between all hosts, were found to be the main source of significant concordance to the observed genetic device performance, whereas specialty genes from respective accessory genomes were not significant. A data-driven investigation revealed that genes involved in denitrification and components of trans-membrane transporter proteins were among the most differentially expressed gene clusters in response to the genetic device. Our results show the chassis-effect can be traced along differences among genome-encoded functions that are mostly conserved and that these differences create a unique biodesign space among closely related species. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/580380v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@173161dorg.highwire.dtl.DTLVardef@b0fdf3org.highwire.dtl.DTLVardef@1f09130org.highwire.dtl.DTLVardef@cc1eb3_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗