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Does genetic diversity protect host populations from parasites? A meta-analysis across natural and agricultural systems

If parasites transmit more readily between closely related hosts, then parasite burdens should decrease with increased genetic diversity of host populations. This important hypothesis is often accepted at face value - notorious epidemics of crop monocultures testify to the vulnerability of host populations that have been purged of diversity. Yet the relationship between genetic diversity and parasitism likely varies across contexts, differing between crop and non-crop hosts and between experimental and natural host populations. Here, we used a meta-analytic approach to ask if host diversity confers protection against parasites over the range of contexts in which it has been tested. We synthesized the results of 102 studies, comprising 2,004 effect sizes representing a diversity of approaches and host-parasite systems. Our results validate a protective effect of genetic diversity, while revealing significant variation in its strength across biological and empirical contexts. In experimental host populations, genetic diversity reduces parasitism by ~20% for non-crop hosts and by ~50% for crop hosts. In contrast, observational studies of natural host populations show no consistent relationship between genetic diversity and parasitism, with both strong negative and positive correlations reported. This result supports the idea that, if parasites preferentially attack close relatives, the correlation of genetic diversity with parasitism could be positive or negative depending upon the potential for host populations to evolve in response to parasite selection. Taken together, these results reinforce genetic diversity as a priority for both conservation and agriculture and emphasize the challenges inherent to drawing comparisons between controlled experimental populations and dynamic natural populations.

Genome-wide association results from: Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology

Late-Onset Alzheimer's disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, and two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value < 5´10-8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways.

Multi-omics analysis reveals the glycolipid metabolism response mechanism in the liver of Genetically Improved Farmed Tilapia (GIFT, Oreochromis niloticus) under hypoxia stress

Background: Dissolved oxygen (DO) in the water is a vital abiotic factor in aquatic animal farming. A hypoxic environment affects the growth, metabolism, and immune system of fish. Glycolipid metabolism is a vital energy pathway under acute hypoxic stress, and it plays a significant role in the adaptation of fish to stressful environments. In this study, we used multi-omics integrative analyses to explore the mechanisms of hypoxia adaptation in Genetically Improved Farmed Tilapia (GIFT, Oreochromis niloticus). Results: The 96 h median lethal hypoxia (96h-LH50) for GIFT was determined by linear interpolation. We established control (DO: 5 mg/L) groups (CG) and hypoxic stress (96h-LH50) groups (HG) and extracted liver tissues for high-throughput transcriptome and metabolome sequencing. A total of 581 differentially expressed (DE) genes and 1250 DE metabolites were detected between CG and HG, and were annotated using tools at the KEGG database. We verified the transcript levels of eight DE genes by quantitative real-time PCR. Conclusions: Analyses of essential glycolipid metabolism pathways of GIFT under hypoxia stress showed that, after 96 h of hypoxia stress, lipid metabolism became the primary metabolic pathway in GIFT. Our findings reveal the changes in metabolites and gene expression that occur under hypoxia stress, and shed light on the regulatory pathways that function under such conditions. Ultimately, this information will be useful to devise strategies to decrease the damage caused by hypoxia stress in farmed fish.

opencc-by-4.0Dec 2019View details →

zenodo36/100

Data and Code: No support for the genetic hypothesis of the Black-white achievement gap using polygenic scores and tests for divergent selection

Data and Code for article "No support for the genetic hypothesis of the Black-white achievement gap using polygenic scores and tests for divergent selection"

Population genetic structure and classification of cultivated and wild pea (Pisum sp.) based on morphological traits and SSR markers

Pea (Pisum sativum L.) is an important legume crop that is widely grown worldwide for human consumption and livestock feed. Despite extensive studies, the population genetic structure and classification of cultivated and wild pea (Pisum sp.) are remaining controversial. To characterize patterns of genetic and morphological variation and investigate the classification of Pisum, we conducted comprehensive population genetic analyses for 323 accessions from cultivated and wild pea representing three species of Pisum utilizing 34 morphological traits and 87 polymorphic SSR markers. First, we identified three distinct genetic groups among all samples. Group I was primarily composed of Pisum fulvum, Pisum abyssinicum and some wild P. sativum accessions, whereas groups II and III consisted of the two genetic groups under P. sativum representing different geographic distributions of cultivated pea. Analyses of morphological variation revealed significant differences among the three species. Second, among pea germplasms representing eight taxa of Pisum, P. fulvum and P. abyssinicum possessed unique genetic backgrounds and morphological characteristics, corroborating their independent species status. The intraspecific subdivisions of P. sativum described by some authors were not supported in this study, with the exception of several genotypes of P. sativum subsp. elatius that were clustered with P. fulvum and P. abyssinicum. Finally, we confirmed that the Chinese pea germplasm was genetically distinct and could be divided into two genetic groups, each of which included both spring-sowing and autumn-sowing ecotypes. These results provide a robust foundation for understanding pea domestication and the utilization of wild genetic resources of pea.

Microsatellite genotypes and associated data for: The contribution of clonality to population genetic structure in the sea anemone Diadumene lineata

Ecological and evolutionary processes differ depending on how genetic diversity is organized in space. For clonal organisms, the organization of both genetic and genotypic diversity can influence the fitness effects of competition, the mating system, and reproductive mode, which are key drivers of life cycle evolution. Understanding how individual reproductive behavior contributes to population genetic structure is essential for disentangling these forces, particularly in species with complex and plastic life cycles. The widespread sea anemone Diadumene lineata exhibits temperature-dependent fission which contributes to predictable variation in clonal rate along the Atlantic coast of the United States, part of its non-native range. Because warmer conditions lead to higher rates of clonality, we expected to find lower genotypic and genetic diversity in lower versus higher latitude populations. We developed primers for 11 microsatellite loci and genotyped 207 anemones collected from 8 sites ranging from Florida to Massachusetts. We found clonal influence at all sites, and as predicted, the largest clones were found at lower latitude sites. We also found genetic signatures of sex in the parts of the range where gametogenesis is most common. Evidence of sex outside the native range is novel for this species and provides insights into the dynamics of this successful invader. Our findings also illustrate challenges that partially clonal taxa pose for eco-evolutionary studies, such as difficulty sampling statistically robust numbers of genets and interpretating common population genetic metrics. For example, we found high among-locus variation in Fis, which makes the meaning of mean multilocus Fis unclear.

opencc-zeroDec 2019View details →

Data for: Feedback between coevolution and epidemiology can help or hinder the maintenance of genetic variation in host-parasite models

Antagonistic coevolution has long been suggested to help maintain host genetic variation. While, ecological and epidemiological feedbacks are known to have important consequences on coevolutionary allele frequency dynamics, their effects on the maintenance of genetic variation remains poorly understood.Here, we extend our previous work on the maintenance of genetic variation in a classic matching-alleles coevolutionary model by exploring the effects of ecological and epidemiological feedbacks, where both allele frequencies and population sizes are allowed to vary over time. We find that coevolution rarely maintains more host genetic variation than expected under neutral genetic drift alone. When and if coevolution maintains or depletes genetic variation relative to neutral drift is determined, predominantly, by two factors: the deterministic stability of the Red Queen allele frequency cycles and the chance of allele fixation in the pathogen, as this results in directional selection and depletion of genetic variation in the host. Compared to purely coevolutionary models with constant host and pathogen population sizes, ecological and epidemiological feedbacks stabilize Red Queen cycles deterministically, but population fluctuations in the pathogen increase the rate of allele fixation in the pathogen, especially in epidemiological models. Our results illustrate the importance of considering the ecological and epidemiological context in which coevolution occurs when examining the impact of Red Queen cycles on genetic variation.

zenodo36/100

Genetic architecture promotes the evolution and maintenance of cooperation

Code and data for Frenoy et al 2013 ("Genetic Architecture Promotes the Evolution and Maintenance of Cooperation" in PLoS Computational Biology)

opencc-by-4.0Nov 2013View details →

Reconstructing hotspots of genetic diversity from glacial refugia and subsequent dispersal in Italian common toads (Bufo bufo)

Genetic diversity feeds the evolutionary process and allows populations to adapt to environmental changes. However, we still lack a thorough understanding of why hotspots of genetic diversity are so 'hot'. Here, we analysed the relative contribution of bioclimatic stability and genetic admixture between divergent lineages in shaping spatial patterns of genetic diversity in the common toad Bufo bufo along the Italian peninsula. We combined population genetic, phylogeographic and species distribution modelling (SDM) approaches to map ancestral areas, glacial refugia, and secondary contact zones. We consistently identified three phylogeographic lineages, distributed in northern, central and southern Italy. These lineages expanded from their ancestral areas and established secondary contact zones, before the last interglacial. SDM identified widespread glacial refugia in peninsular Italy, sometimes located under the present-day sea-level. Generalized linear models indicated genetic admixture as the only significant predictor of the levels of population genetic diversity. Our results show that glacial refugia contributed to preserving both levels and patterns of genetic diversity across glacial-interglacial cycles, but not to their formation, and highlight a general principle emerging in Mediterranean species: higher levels of genetic diversity mark populations with substantial contributions from multiple genetic lineages, irrespective of the location of glacial refugia.

Identifying diagnostic genetic markers for a cryptic invasive agricultural pest: a test case using the apple maggot fly, Rhagoletis pomonella (Diptera: Tephritidae)

Insect pests destroy ~15% of all USA crops, resulting in losses of $15 billion annually. Thus, developing cheap, quick and reliable methods for detecting harmful species is critical to curtail insect damage and lessen economic impact. The apple maggot fly, Rhagoletis pomonella (Diptera: Tephritidae), is a major invasive pest threatening the multibillion-dollar apple industry in the Pacific Northwest USA. The fly is also sympatric with a benign but morphologically similar and genetically closely related species, R. zephyria, which attacks non-commercial snowberry. Unambiguous species identification is essential due to a zero-infestation policy of apple maggot for fruit export. Mistaking R. zephyria for R. pomonella triggers unnecessary and costly quarantines, diverting valuable control resources. Here we develop and apply a relatively simple and cost-effective diagnostic approach using Illumina sequencing of double digest restriction-site associated DNA markers. We identified five informative single nucleotide polymorphisms (SNPs) and designed a diagnostic test based on agarose gel electrophoresis of restriction enzyme digested polymerase chain reaction amplification products (RFLPs) to distinguish fly species. We demonstrated the utility of this approach for immediate, one day species identification by scoring apple- and snowberry-infesting flies of known host plant identity, reared directly from 11 sites throughout Washington. However, if immediate diagnosis is not required, or hundreds to thousands of specimens must be assessed, then a direct Illumina-based sequencing strategy, similar to that used here for diagnostic SNP identification can be powerful and cost-effective. The genomic strategy we present is effective for R. pomonella and also transferable to many cryptic pests.

Positive genetic covariance between male sexual ornamentation and fertilizing capacity

Postcopulatory sexual selection results from variation in competitive fertilization success among males, and comprises powerful evolutionary forces that operate after the onset of mating [1, 2]. Theoretical advances in the field of sexual selection addressing the build-up and co-evolutionary consequences of genetic coupling [3-5], motivate the hypothesis that indirect postcopulatory sexual selection may promote evolution of male secondary sexual traits—those traits traditionally ascribed to mate choice and male fighting [6, 7]. A crucial prediction of this hypothesis is genetic covariance between trait expression and competitive fertilization success, which has been predicted to arise, for example, when traits subject to pre- and postcopulatory sexual selection are under positive correlational selection [8]. We imposed bidirectional artificial selection on male ornament (sex comb) size in Drosophila bipectinata, and demonstrate increased competitive fertilization success as a correlated evolutionary response to increasing ornament size. Transcriptional analyses revealed that levels of specific seminal fluid proteins repeatedly shifted in response to this selection, suggesting that properties of the ejaculate rather than the enlarged sex comb itself contributed fertilizing capacity. We used ultraprecise laser surgery to reduce ornament size of high line males, and found that their fertilizing superiority persisted despite the size reduction, reinforcing the transcriptional results. The data support the existence of positive genetic covariance between a male secondary sexual trait and competitive fertilization success, and suggest the possibility that indirect postcopulatory sexual selection may under certain conditions magnify net selection on ornamental trait expression.

The genetic basis of coordinated plasticity across functional units in a Lake Malawi cichlid mapping population

Adaptive radiations are often stereotypical, as populations repeatedly specialize along conserved environmental axes. Phenotypic plasticity may be similarly stereotypical, as individuals respond to environmental cues. These parallel patterns of variation, which are often consistent across traits, have led researchers to propose that plasticity can facilitate predictable patterns of evolution along environmental gradients. This "flexible stem" model of evolution raises questions about the genetic nature of plasticity, including: How complex is the genetic basis for plasticity? Is plasticity across traits mediated by many distinct loci, or few "global" regulators? To address these questions, we reared a hybrid cichlid mapping population on alternate diet regimes mimicking an important environmental axis. We show that plasticity across an array of ecologically relevant traits is generally morphologically integrated, such that traits respond in a coordinated manner, especially those with overlapping function. Our genetic data are more ambiguous. While our mapping experiment provides little evidence for global genetic regulators of plasticity, these data do contain a genetic signal for the integration of plasticity across traits. Overall, our data suggest a compromise between genetic modularity, whereby plasticity may evolve independently across traits, and low-level but widespread genetic integration, establishing the potential for plasticity to experience coordinated evolution.

Mapping the geographic origin of captive and confiscated Hermann's tortoises: a genetic toolkit for conservation and forensic analyses

The illegal trade has been threatening tortoise populations worldwide for decades. Nowadays, however, DNA typing and forensic genetic approaches allow us to investigate the geographic origin of confiscated animals and to relocate them into the wild, providing that suitable molecular tools and reference data are available. Here we assess the suitability of a small panel of microsatellite markers to investigate patterns of illegal translocations and to assist forensic genetic applications in the endangered Mediterranean land tortoise Testudo hermanni hermanni. Specific allelic ladders were created for each locus and tested on several reference samples. We used the microsatellite panel to (i) increase our understanding of the population genetic structure in wild populations with new data from previously unsampled geographic areas (overall 461 wild individuals from 28 sampling sites); (ii) detect the presence of non-native individuals in wild populations; and (iii) identify the most likely geographic area of origin of 458 confiscated individuals hosted in Italian seizure and recovery centers. Our analysis initially identified six major genetic clusters corresponding to different geographic macro-areas along the Mediterranean range. Long-distance migrants among wild populations, due to translocations, were found and removed from the reference database. Assignment tests allowed us to allocate approximately 70% of confiscated individuals of unknown origin to one of the six Mediterranean macro-areas. Most of the assigned tortoises belonged to the genetic cluster corresponding to the area where the respective captivity center was located. However, we also found evidence of long-distance origins of confiscated individuals, especially in centers along the Adriatic coast and facing the Balkan regions, a well-known source of illegally traded individuals. Our results clearly show that the microsatellite panel and the reference dataset can play a beneficial role in reintroduction and repatriation projects when confiscated individuals need to be re-assigned to their respective macro-area of origin before release, and can assist future forensic genetic applications in detecting the illegal trade and possession of Testudo hermanni individuals.

The Camouflage Machine: Optimising protective colouration using deep learning with genetic algorithms

Evolutionary biologists frequently wish to measure the fitness of alternative phenotypes using behavioural experiments. However, many phenotypes are complex. For example colouration: camouflage aims to make detection harder, while conspicuous signals (e.g. for warning or mate attraction) require the opposite. Identifying the hardest and easiest to find patterns is essential for understanding the evolutionary forces that shape protective colouration, but the parameter space of potential patterns (coloured visual textures) is vast, limiting previous empirical studies to a narrow range of phenotypes. Here we demonstrate how deep learning combined with genetic algorithms can be used to augment behavioural experiments, identifying both the best camouflage and the most conspicuous signal(s) from an arbitrarily vast array of patterns. To show the generality of our approach, we do so for both trichromatic (e.g. human) and dichromat (e.g. typical mammalian) visual systems, in two different habitats. The patterns identified were validated using human participants; those identified as the best for camouflage were significantly harder to find than a tried-and-tested military design, while those identified as most conspicuous were significantly easier than other patterns. More generally, our method, dubbed the 'Camouflage Machine', will be a useful tool for identifying the optimal phenotype in high dimensional state-spaces.

The genetic basis of cytoplasmic male sterility and fertility restoration in wheat

Hybrid wheat varieties give higher yields than conventional lines but are difficult to produce due to a lack of effective control of male fertility in breeding lines. One promising system involves the Rf1 and Rf3 genes that restore fertility of wheat plants carrying Triticum timopheevii-type cytoplasmic male sterility (T-CMS). By genetic mapping and comparative sequence analyses we identified Rf1 and Rf3 candidates that could restore normal pollen production in transgenic wheat plants carrying T-CMS. We show that Rf1 and Rf3 bind to the mitochondrial orf279 transcript and induce cleavage, preventing expression of the CMS trait. The identification of restorer genes in wheat is an important step towards the development of hybrid wheat varieties based on a CMS-Rf system. The characterisation of their mode of action brings new insights into the molecular basis of CMS and fertility restoration in plants. This dataset includes transcript count and coverage data from 2 RNA-seq experiments looking at gene expression in various male-sterile or male-fertile wheat lines examined in the course of this research.

opencc-by-4.0Jun 2020View details →

zenodo36/100

m6A-TWAS weights for "Genetic Analyses Support the Contribution of mRNA N6-methyladenosine (m6A) Modification to Human Diseases Heritability"

We included the m6A-TWAS weights (trained using FUSION) for our manuscript "Genetic Analyses Support the Contribution of mRNA N6-methyladenosine (m6A) Modification to Human Diseases Heritability".  This dataset is a supplement to the m6A QTL summary statistics data and imputed genotype data at https:// doi.org/10.5281/zenodo.3870952.

Weak genetic signal for phenotypic integration implicates developmental processes as major regulators of trait covariation

Phenotypic integration is an important metric that describes the degree of covariation among traits in a population, and is hypothesized to arise due to selection for shared functional processes. Our ability to identify the genetic and/or developmental underpinnings of integration is marred by temporally overlapping cell-, tissue-, and structure-level processes that serve to continually 'overwrite' the structure of covariation among traits through ontogeny. Here we examine whether traits that are integrated at the phenotypic level, also exhibit a shared genetic basis (e.g., pleiotropy). We micro-CT scanned two hard tissue traits, and two soft tissue traits (mandible, pectoral girdle, atrium, and ventricle respectively) from an F5 hybrid population of Lake Malawi cichlids, and used geometric morphometrics to extract 3D shape information from each trait. Given the large degree of asymmetric variation that may reflect developmental instability, we separated symmetric- from asymmetric-components of shape variation. We then performed quantitative trait loci (QTL) analysis to determine the degree of genetic overlap between shapes. While we found ubiquitous associations among traits at the phenotypic level, except for a handful of notable exceptions, our QTL analysis revealed few overlapping genetic regions. Taken together, this indicates developmental interactions can play a large role in determining the degree of phenotypic integration among traits, and likely obfuscate the genotype to phenotype map, limiting our ability to gain a comprehensive picture of the genetic contributors responsible for phenotypic divergence.

Small fish, large river: surprisingly minimal genetic structure in a dispersal-limited, habitat specialist fish

Genetic connectivity is expected to be lower in species with limited dispersal ability and a high degree of habitat specialization (intrinsic factors). Also, gene flow is predicted to be limited by habitat conditions such as physical barriers and geographic distance (extrinsic factors). We investigated the effects of distance, intervening pools, and rapids on gene flow in a species, the Tuxedo Darter (Etheostoma lemniscatum), a habitat specialist that is presumed to be dispersal-limited. We predicted that the interplay between these intrinsic and extrinsic factors would limit dispersal and lead to genetic structure even at the small spatial scale of the species range (a 38.6 km river reach). The simple linear distribution of E. lemniscatum allowed for an ideal test of how these factors acted on gene flow and allowed us to test expectations (e.g., isolation-by-distance) of linearly distributed species. Using 20 microsatellites from 163 individuals collected from 18 habitat patches, we observed low levels of genetic structure that were related to geographic distance and rapids, though these factors were not barriers to gene flow. Pools separating habitat patches did not contribute to any observed genetic structure. Overall, E. lemniscatum maintains gene flow across its range and is comprised of a single population. Due to the linear distribution of the species, a stepping stone model of dispersal best explains the maintenance of gene flow across its small range. In general, our observation of higher than expected connectivity likely stems from an adaptation to disperse due to temporally unstable and patchy habitat.

Analysing landscape effects on dispersal networks and gene flow with genetic graphs

Graph-theoretic approaches have relevant applications in landscape genetic analyses. When species form populations in discrete habitat patches, genetic graphs can be used i) to identify direct dispersal paths followed by propagules or ii) to quantify landscape effects on multigenerational gene flow. However, the influence of their construction parameters remains to be explored. Using a simulation approach, we constructed genetic graphs using several pruning methods (geographical distance thresholds, topological constraints, statistical inference) and genetic distances to weight graph links (FST, DPS, Euclidean genetic distances). We then compared the capacity of these different graphs to i) identify the precise topology of the dispersal network and ii) to infer landscape resistance to gene flow from the relationship between cost-distances and genetic distances. Although not always clear-cut, our results showed that methods based on geographical distance thresholds seem to better identify dispersal networks in most cases. More interestingly, our study demonstrates that a subselection of pairwise distances through graph pruning (thereby reducing the number of data points) can counter-intuitively lead to improved inferences of landscape effects on dispersal. Finally, we showed that genetic distances such as the DPS or Euclidean genetic distances should be preferred over the FST for landscape effect inference as they respond faster to landscape changes.

Genetic diversity in two insular populations of bobcats (Lynx rufus)

We documented changes in genetic diversity in an isolated, reintroduced population of bobcats on Cumberland Island (CUIS), Georgia, USA, compared to another bobcat population on Kiawah Island, South Carolina, USA, that was naturally established and experiences limited immigration from the mainland. We compared the predictions of a novel population viability analysis (PVA) to empirical estimates of abundance and genetic diversity on CUIS and used our PVA to identify management actions that are likely to support long-term viability.