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bioRxiv2016

Sex differences in disease genetics

There is long-standing evidence for gene-by-sex interactions in disease risk, which can now be tested in genome-wide association studies with participant numbers in the hundreds of thousands. Contemporary methods start with a separate test for each sex, but simulations suggest a more powerful approach should be to use sex as an interaction term in a single test. The traits currently with the most compelling evidence for sex-dependent genetic effects are for adiposity (predictive of cardiac disease), type II diabetes, asthma and inflammatory bowel disease. Sexually dimorphic gene expression varies dynamically, by age, tissue type, and chromosome, so sex dependent genetic effects are expected for a wide range of diseases.\n\nKey conceptsO_LICompelling findings of sex-dependent genetic effects on disease have been made in adiposity-related anthropometric traits, type II diabetes, and inflammatory bowel disease. Other disorders remain to be more fully investigated, regardless of what sexual differences they exhibit in prevalence and presentation.\nC_LIO_LICurrent evidence indicates that sex difference in gene expression is not required for a SNP to have a sex-dependent effect. However, sex differences in gene expression vary dynamically, by organ and age, so generalisations may be inaccurate without comprehensive data.\nC_LIO_LISex-dependent risk alleles are predicted to be of greater effect size than conventional ones, because natural selection acts only against the sex which has the disease. There is evidence for this from a high-powered GWAS of adiposity-related traits.\nC_LIO_LIMany of the large GWAS meta-analyses look for sex-dependent genetic effects by testing male and female groups separately. However, this may be under-powered compared to a whole-sample, gene-by-sex interaction test.\nC_LI\n\nGlossaryO_LIGenome-wide association study (GWAS). Method for identifying molecular genetic variation that controls heritable traits, in a population sample. Involves assessing the correlation between allele frequencies and phenotype value, at millions of markers of common genetic variation across the genome.\nC_LIO_LISexual dimorphism. A difference between males and females in a population for the value of a particular trait. May include anything from anatomical measurements to expression level of a gene.\nC_LIO_LISex-dependent genetic effect. A disease risk allele is termed sex-specific when it increases risk in one sex only but has no effect on the disease in the other sex. The term sex-biased is used for an allele causes a significant increase in risk of disease in both sexes, but for which the magnitude of the risk increase is significantly different between males and females. There are also reports where an allele that increases risk of a disease in one sex reduces risk of the same disease in the other sex but none have been replicated, and there is no biochemical reason why this could be true. It effectively constitutes a sexually antagonistic effect, but should be distinguished from intra-locus sexual conflict which explicitly requires than an allele have opposing effects on the evolutionary fitness of males and females (Bonduriansky and Chenoweth 2009). All of the above relationships constitute a form of sex-dependent genetic effect.\nC_LI

Genetics↗

bioRxiv2016

Visualizing the Geography of Genetic Variants

One of the key characteristics of any genetic variant is its geographic distribution. The geographic distribution can shed light on where an allele first arose, what populations it has spread to, and in turn on how migration, genetic drift, and natural selection have acted. The distribution of a genetic variant can also be of great utility for medical/clinical geneticists. Collectively the geographic distribution of many genetic variants can reveal population structure. As a result, visual inspection of geographic maps for genetic variants is common practice in genetic studies. Here we develop an interactive visualization tool for rapidly displaying the geographic distribution of genetic variants. Through a REST API and dynamic front-end the Geography of Genetic Variants (GGV) browser provides maps of allele frequencies in populations distributed across the globe.

Genetics↗

bioRxiv2016

Evidence that low socioeconomic position accentuates genetic susceptibility to obesity

Susceptibility to obesity in todays environment has a strong genetic component. Lower socioeconomic position (SEP) is associated with a higher risk of obesity but it is not known if it accentuates genetic susceptibility to obesity. We aimed to use up to 120,000 individuals from the UK Biobank study to test the hypothesis that measures of socioeconomic position accentuate genetic susceptibility to obesity. We used the Townsend deprivation index (TDI) as the main measure of socioeconomic position, and a 69-variant genetic risk score (GRS) as a measure of genetic susceptibility to obesity. We also tested the hypothesis that interactions between BMI genetics and socioeconomic position would result in evidence of interaction with individual measures of the obesogenic environment and behaviours that correlate strongly with socioeconomic position, even if they have no obesogenic role. These measures included self-reported TV watching, diet and physical activity, and an objective measure of activity derived from accelerometers. We performed several negative control tests, including a simulated environment correlated with BMI but not TDI, and sun protection use. We found evidence of gene-environment interactions with TDI (Pinteraction=3x10-10) such that, within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. We also observed evidence of interaction between sun protection use and BMI genetics, suggesting that residual confounding may result in evidence of non-causal interactions. Our findings provide evidence that relative social deprivation best captures aspects of the obesogenic environment that accentuate the genetic predisposition to obesity in the UK.

Genetics↗

bioRxiv2017

Genetical genomics reveals Ras/MAPK modifier loci

The oncogenic Ras/MAPK pathway is evolutionary conserved across metazoans and is essential for many cellular functions. Mutant screens in the model nematode Caenorhabditis elegans have been invaluable for elucidating Ras/MAPK pathway characteristics and identification of the genes involved. Almost all of these screens have been conducted in a single genetic background. However, phenotypic traits of induced mutations can vary widely depending on the genetic background. At the moment, we lack insight into how different genetic backgrounds modulate Ras/MAPK-signaling and which genetic modifiers are involved.\n\nWe previously introduced a gain-of-function mutation in the Ras/MAPK pathway gene let-60 in over 200 recombinant inbred lines (mutant introgressed RILs: miRILs) and detected genetic modifiers affecting this pathway by studying variation in vulval development. In the present study, we investigate how gene expression regulation is affected by the let-60 gain-of-function mutation and the genetic background by mapping eQTL using 33 miRILs. We found that the majority ([~]73%) of the 1516 detected cis-eQTL are not specific for the let-60 mutation, whereas most ([~]76%) of the 898 detected trans-eQTL are associated with the let-60 mutation. We detected 6 eQTL trans-bands that were specific for the interaction between the genetic background and the mutation. One of these eQTL hotspots co-localizes with the previously identified polymorphic Ras/MAPK modifier amx-2. Comparing gene expression profiles between transgenic lines expressing either the N2 or the CB4856 alleles of amx-2 showed the involvement of amx-2 in 79% of the trans-eQTLs for genes mapping to this trans-band.\n\nTogether, our results have revealed hidden loci affecting Ras/MAPK signaling using sensitized backgrounds in C. elegans. These loci harbor putative polymorphic modifier genes that would not have been detected using mutant screens in single genetic backgrounds.

genetics↗

bioRxiv2017

Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records

Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally-ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3,330 BD cases and 3,952 controls of European ancestry were used to estimate SNP-based heritability (h2g) and genetic correlation(rg) between EHR-based phenotype definitions and traditionally-ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and 3 rule-based algorithms using codified EHR with decreasing levels of stringency - \"coded-strict\", \"coded-broad\", and \"coded-broad based on a single clinical encounter\" (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1,968 coded-strict, 2,581 coded-broad, 408 coded-broad-SV BD cases, and 3,952 controls. The estimated h2g were 0.24 (p=0.015), 0.09 (p=0.064), 0.13 (p=0.003), 0.00 (p=0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h2g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h2g) was 0.12 (p=0.004). These h2g were lower or similar to the h2g observed by the ICCBD+PGCBD (0.23, p=3.17E-80, total N=33,181). However, the rg between ICCBD+PGCBD and the EHR-based cases were high for 95-NLP (0.66, p=3.69x10-5), coded-strict (1.00, p=2.40x10-4), and coded-broad (0.74, p=8.11x10-7). The rg between EHR-based BDs ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research.

genetics↗

bioRxiv2017

Age at first birth in women is genetically associated with increased risk of schizophrenia

Previous studies have shown an increased risk for a range of mental health issues in children born to both younger and older parents compared to children of average-aged parents. However, until recently, it was not clear if these increased risks are due to psychosocial factors associated with age or if parents at higher genetic risk for psychiatric disorders tend to have children at an earlier or later age. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age of mothers at the birth of their first child (AFB). Here, we use independent data from the UK Biobank (N=38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, end to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value=1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value=3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE=0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE=0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.

genetics↗

bioRxiv2018

The Shared Genetic Basis of Human Fluid Intelligence and Brain Morphology

Individual differences in educational attainment are linked to differences in intelligence, and predict important social, economic and health outcomes. Previous studies have found common genetic factors that influence educational achievement, cognitive performance and total brain volume (i.e., brain size). Here, in a large sample of participants from the UK Biobank, we investigate the shared genetic basis between educational attainment and fine-grained cerebral cortical morphological features, and associate this genetic variation with a related aspect of cognitive ability. Importantly, we execute novel statistical methods that enable high-dimensional genetic correlation analysis, and compute high-resolution surface maps for the genetic correlations between educational attainment and vertex-wise morphological measurements. We conduct secondary analyses, using the UK Biobank verbal-numerical reasoning score, to confirm that variation in educational attainment that is genetically correlated with cortical morphology is related to differences in cognitive performance. Our analyses reveal the genetic overlap between cognitive ability and cortical thickness measurements in bilateral primary motor cortex and predominantly left superior temporal cortex and proximal regions. These findings may contribute to our understanding of the neurobiology that connects genetic variation to individual differences in educational attainment and cognitive performance.

genetics↗

bioRxiv2018

The Limits to Parapatric Speciation II: Strengthening a Preexisting Genetic Barrier to Gene Flow in Parapatry

Parapatric speciation has recently received a lot of attention. By encompassing the whole continuum between allopatric and sympatric scenarios, it includes many potential scenarios for the evolution of new species. Building upon previous work, we investigate how a genetic barrier to gene flow, that relies on a single postzygotic genetic incompatibility, may further evolve. We consider a continent island model with three loci involved in pairwise Dobzhansky-Muller incompatibilities (DMIs). Using a deterministic and analytic approach, we derive the conditions for invasion of a new mutation and its consequences on an already existing genetic barrier to gene flow. We focus on quantifying the impact of the epistasis generated by the new mutation on the genetic barrier. We show that the accumulation of genetic incompatibilities in the presence of gene flow is a complex process, where new mutations can either strengthen or destroy a preexisting barrier. In particular, preexisting polymorphism and incompatibilities do not always facilitate the growth of the genetic barrier by accumulation of further barrier genes. Migration may disrupt the snowball effect (the accelerating rate of DMI accumulation in allopatry) because incompatibilities are directly tested by selection. Our results also show an ambiguous role of gene flow, which can either impede or facilitate the strengthening of the genetic barrier. Overall, our results illustrate how the inclusion of gene flow renders the building of a genetic barrier difficult to analyze.

genetics↗

bioRxiv2018

A High-Resolution Genetic Map for the Laboratory Rat

An accurate and high-resolution genetic map is critical for mapping complex traits, yet the resolution of the current rat genetic map is far lower than human and mouse, and has not been updated since the original ensen-Seaman map in 2004. For the first time, we have refined the rat genetic map to sub-centimorgan (cM) r solution (<0.02 cM) by using 95,769 genetic markers and 870 informative meioses from a cohort of 528 heterogeneous stock (HS) rats. Global recombination rates in the revised sex-averaged map (0.66 cM/Mb) did not difeer compared to the historical map (0.65 cM/Mb); however, substantial refinement was made to the localization of highly recombinant regions within the revised map. Also for the first time, sex-specific rat genetic maps were generated, which revealed both genomewide and fine-scale variation in recombination rates between male and female rats. Reanalysis of multiple quantitative trait loci (QTL) using the historical and refined rat genetic maps demonstrated marked changes to QTL localization, shape, and effect size. As a resource to the rat research community, we have provided revised centimorgan positions for all physical positions within the rat genome and commonly used genetic markers for trait mapping, including 44,828 SSLP markers and the RATDIV genotyping array. Collectively, this study provides a substantial improvement to the rat genetic map and an unprecedented resource for analysis of complex traits and recombination in the rat.

genetics↗

bioRxiv2018

Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

Sprague Dawley (SD) rats are among the most widely used outbred laboratory rat populations. Despite this, the genetic characteristics of SD rats have not been clearly described, and SD rats are rarely used for experiments aimed at exploring genotype-phenotype relationships. In order to use SD rats to perform a genome-wide association study (GWAS), we collected behavioral data from 4,625 SD rats that were predominantly obtained from two commercial vendors, Charles River Laboratories and Harlan Sprague Dawley Inc. Using double-digest genotyping-by-sequencing (ddGBS), we obtained dense, high-quality genotypes at 291,438 SNPs across 4,061 rats. This genetic data allowed us to characterize the variation present in Charles River vs. Harlan SD rats. We found that the two populations are highly diverged (FST > 0.4). Furthermore, even for rats obtained from the same vendor, there was strong population structure across breeding facilities and even between rooms at the same facility. We performed multiple separate GWAS by fitting a linear mixed model that accounted population structure and using meta-analysis to jointly analyze all cohorts. Our study examined Pavlovian conditioned approach (PavCA) behavior, which assesses the propensity for rats to attribute incentive salience to reward-associated cues. We identified 46 significant associations for the various metrics used to define PavCA. The surprising degree of population structure among SD rats from different sources has important implications for their use in both genetic and non-genetic studies. Author SummaryOutbred Sprague Dawley rats are among the most commonly used rats for neuroscience, physiology and pharmacological research; in the year 2020, 4,188 publications contained the keyword "Sprague Dawley". Rats identified as "Sprague Dawley" are sold by several commercial vendors, including Charles River Laboratories and Harlan Sprague Dawley Inc. (now Envigo). Despite their widespread use, little is known about the genetic diversity of SD. We genotyped more than 4,000 SD rats, which we used for a genome-wide association study (GWAS) and to characterize genetic differences between SD rats from Charles River Laboratories and Harlan. Our analysis revealed extensive population structure both between and within vendors. The GWAS for Pavlovian conditioned approach (PavCA) identified a number of genome-wide significant loci for that complex behavioral trait. Our results demonstrate that, despite sharing an identical name, SD rats that are obtained from different vendors are very different. Future studies should carefully define the exact source of SD rats being used and may exploit their genetic diversity for genetic studies of complex traits.

genetics↗

bioRxiv2017

Genetic And Epigenetic Insight Into Morphospecies In A Reef Coral

Incongruence between conventional and molecular systematics has left the delineation of many species unresolved. Reef-building corals are no exception, with phenotypic plasticity among the most plausible explanations for alternative morphospecies. As potential molecular signatures of phenotypic plasticity, epigenetic processes may contribute to our understanding of morphospecies. We compared genetic and epigenetic variation in Caribbean branching Porites spp., testing the hypothesis that epigenetics-- specifically, differential patterns of DNA methylation--play a role in alternative morphotypes of a group whose taxonomic status has been questioned. We used reduced representation genome sequencing to analyze over 1,000 single nucleotide polymorphisms and CpG sites in 27 Porites spp. exhibiting a range of morphotypes from a variety of habitats in Belize. We found stronger evidence for genetic rather than epigenetic structuring, identifying three well-defined genetic groups. One of these groups exhibited significantly thicker branches, and branch thickness was a better predictor of genetic groups than depth, habitat, or symbiont type. Epigenetic patterns were more subtle, with no clear groups. The more thickly branched individuals in one of the genetic groups exhibited some epigenetic similarity, suggesting potential covariation of genetics and epigenetics. This covariation was further supported by a positive association between pairwise genetic and epigenetic distance. We speculate that epigenetic patterns are a complex mosaic reflecting inheritance and diverse environmental histories. Given the role of genetics in branching Porites spp. morphospecies we were able to detect with genome-wide sequencing, use of such techniques throughout the geographic range may help settle their phylogeny.

molecular biology↗

bioRxiv2017

Disease as collider: a new case-only method to discover environmental factors in complex diseases with genetic risk estimation

BackgroundCase-only design for gene-environment interaction (CODGEI) relies on the rare disease assumption. A negative association due to collider bias appears between gene and environment when this assumption is not respected. Genetic risk estimation can quantify part of the predisposition of an individual to a disease.\n\nMethodsWe introduce Disease As Collider (DAC), a new case-only methodology to discover environmental factors using genetic risk estimation: a negative correlation between genetic risk and environment in cases provides a signature of a genuine environmental risk marker. Simulation of disease occurrence in a source population allows to estimate the statistical power of DAC and the influence of collider bias in CODGEI. We illustrate DAC in 831 type 1 diabetes (T1D) patients. Results: The power of DAC increases with sample size, prevalence and accuracy of genetic risk estimation. For a prevalence of 1% and a realistic genetic risk estimation, power of 80% is reached for a sample size under 3000. Collider bias offers an alternative interpretation to the results of CODGEI in a published study on breast cancer.\n\nConclusionDAC could provide a new line of evidence for discovering which environmental factors play a role in complex diseases or confirming results obtained in case-control studies. We discuss the circumstances needed for DAC to participate in the dissection of environmental determinants of disease. We provide guidance on the use of CODGEI regarding the rare disease assumption.\n\nO_LSTKey messagesC_LSTO_LIA complex disease is a collider between genetic determinants and environmental factors; it is a consequence of both.\nC_LIO_LICollider bias can affect the results of the case-only design for gene-environment interactions when the disease is common.\nC_LIO_LIUsing genetic risk estimation, collider bias can be used to discover or confirm the association between a disease and an environmental factor in a case-only setting.\nC_LIO_LIStatistical power of this approach is small when the disease is rare. Power increases with sample size, prevalence and genetic risk prediction accuracy.\nC_LI

epidemiology↗

bioRxiv2017

A Century of Guayule: Comprehensive Genetic Characterization of the Guayule (Parthenium argentatum A. Gray) USDA Germplasm Collection

The fragility of a single-source, geographically concentrated supply of natural rubber, a critical material of the modern economy, has brought guayule (Parthenium argentatum A. Gray) to the forefront as an alternative source of natural rubber. The improvement of guayule for commercial-scale production has been limited by the lack of genomic tools and well-characterized genetic resources required for genomics-assisted breeding. To address this issue, we developed nearly 50,000 single nucleotide polymorphism (SNP) genetic markers and genotyped 69 accessions of guayule and its sister taxa mariola (Parthenium incanum Kunth), representing the entire available NALPGRU germplasm collection. We identified multiple interspecific hybrid accessions previously considered guayule, including six guayule-mariola hybrids and non-mariola interspecific hybrid accessions AZ-2 and AZ-3, two commonly used high-yielding cultivars. We dissected genetic diversity within the collection to identify a highly diverse subset of guayule accessions, and showed that wild guayule stands in Big Bend National Park, Texas, USA have the potential to provide hitherto untapped guayule genetic diversity. Together, these results provide the most thorough genetic characterization of guayule germplasm to date and lay the foundation for rapid genetic improvement of commercial guayule germplasm.\n\nKey Results O_LISix guayule accessions are guayule-mariola hybrids\nC_LIO_LIGuayule collections from Big Bend National Park contain novel guayule genotypes not present in collections from Mexico\nC_LIO_LICommonly cultivated accessions AZ2 and AZ3 contain introgressions from other Parthenium species\nC_LIO_LIThe triploid accessions 11591, 11646, N576, N565, N565II, and RICHARDSON are generally indistinguishable from each other with respect to genetic background and likely represent the 4265-I source genotype (Johnson, 1950)\nC_LIO_LIOpen pollinated and purposefully outcrossed tetraploid selections derived from 4265-I incorporate further genetic diversity and form distinct genotypes\nC_LI

plant biology↗

bioRxiv2017

Dissecting Population Substructure in India via Correlation Optimization of Genetics and Geodemographics

India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification. While geography closely correlates with genetic structure in other parts of the world, the strict endogamy imposed by the Indian caste system and the large number of spoken languages add further levels of complexity to understand Indian population structure. To date, no study has attempted to model and evaluate how these factors have interacted to shape the patterns of genetic diversity within India. We merged all publicly available data from the Indian subcontinent into a data set of 891 individuals from 90 well-defined groups. Bringing together geography, genetics and demographic factors, we developed COGG (Correlation Optimization of Genetics and Geodemographics) to build a model that explains the observed population genetic substructure. We show that shared language along with social structure have been the most powerful forces in creating paths of gene flow in the subcontinent. Furthermore, we discover the ethnic groups that best capture the diverse genetic substructure highlighted by COGG. Integrating data from India with a data set of additional 1,323 individuals from 50 populations we find that Europeans show shared genetic drift with the Indo-European and Dravidian speakers of India, whereas the East Asians have the maximum shared genetic drift with Tibeto-Burman speaking tribal groups.

genomics↗

bioRxiv2017

Inferring Continuous and Discrete Population Genetic Structure Across Space

A classic problem in population genetics is the characterization of discrete population structure in the presence of continuous patterns of genetic differentiation. Especially when sampling is discontinuous, the use of clustering or assignment methods may incorrectly ascribe differentiation due to continuous processes (e.g., geographic isolation by distance) to discrete processes, such as geographic, ecological, or reproductive barriers between populations. This reflects a shortcoming of current methods for inferring and visualizing population structure when applied to genetic data deriving from geographically distributed populations. Here, we present a statistical framework for the simultaneous inference of continuous and discrete patterns of population structure. The method estimates ancestry proportions for each sample from a set of two-dimensional population layers, and, within each layer, estimates a rate at which relatedness decays with distance. This thereby explicitly addresses the \"clines versus clusters\" problem in modeling population genetic variation. The method produces useful descriptions of structure in genetic relatedness in situations where separated, geographically distributed populations interact, as after a range expansion or secondary contact. We demonstrate the utility of this approach using simulations and by applying it to empirical datasets of poplars and black bears in North America.\n\nAuthor summaryOne of the first steps in the analysis of genetic data, and a principal mission of biology, is to describe and categorize natural variation. A continuous pattern of differentiation (isolation by distance), where individuals found closer together in space are, on average, more genetically similar than individuals sampled farther apart, can confound attempts to categorize natural variation into groups. This is because current statistical methods for assigning individuals to discrete clusters cannot accommodate spatial patterns, and so are forced to use clusters to describe what is in fact continuous variation. As isolation by distance is common in nature, this is a substantial shortcoming of existing methods. In this study, we introduce a new statistical method for categorizing natural genetic variation - one that describes variation as a combination of continuous and discrete patterns. We demonstrate that this method works well and can capture patterns in population genomic data without resorting to splitting populations where they can be described by continuous patterns of variation.

evolutionary biology↗

bioRxiv2017

Incipient signs of genetic differentiation among African elephant populations in fragmenting miombo ecosystems in south-western Tanzania

Habitat fragmentation plays a major role in the reduction of genetic diversity among wildlife populations. The African savannah elephant population of the Ruaha-Rungwa and Katavi-Rukwa ecosystems in south-western Tanzania, comprises one of the worlds largest remaining elephant populations, but is increasingly threatened by loss of connectivity and poaching for ivory. We investigate whether there are incipient signs of genetic isolation (loss of heterozygosity) within the younger cohort as a result of habitat loss between the two ecosystems. To investigate the genetic structure of populations, we compared the genotypes for 11 microsatellite loci in the western (n = 81 individuals from Katavi-Rukwa), central (n = 36 individuals from Lukwati and Piti), and eastern populations (n = 193, individuals from Ruaha-Rungwa). We found evidence of significant genetic differentiation among the three populations, but the levels were low, suggesting recent divergence. Furthermore, we identified weak isolation by distance, suggesting higher gene flow among nearer individuals with samples within 50km of each other being more genetically similar to one another than beyond. Although sample sizes were small, a further analysis of genetic differences across populations and in separate age classes revealed evidence of increasing genetic structure among younger age classes across the landscape. In a long-lived species with overlapping generations, it takes a long time to develop genetic substructure even when there are substantial obstacles to migration. Thus, in these recently fragmented populations, inbreeding (and the loss of heterozygosity) may be less of an immediate concern than demography (the loss of adults due to illegal hunting).

ecology↗

bioRxiv2018

Genetic and environmental influence on the human functional connectome

Detailed mapping of genetic and environmental influences on the functional connectome is a crucial step toward developing intermediate phenotypes between genes and clinical diagnoses or cognitive abilities. We analyze resting-state data from two, adult twin samples - 390 twins from the Colorado Longitudinal Twin Sample and 422 twins from the Human Connectome Project - to examine genetic and environmental influence on all pairwise functional connections between 264 brain regions (~35,000 functional connections). Non-shared environmental influence was high, genetic influence was moderate, and shared environmental influence was weak-to-moderate across the connectome. The brains genetic organization is diverse and not as one would expect based solely on structure evident in non-genetically informative data or lower-resolution data. As follow-up, we make novel classifications of functional connections and examine highly-localized connections with particularly strong genetic influence. This high-resolution genetic taxonomy of brain connectivity will be useful in understanding genetic influences on brain disorders.

neuroscience↗

bioRxiv2018

Flow regulation associated with decreased genetic health of a river-breeding frog species

River regulation or flow modification--the hydrological alteration of flow by dams and diversions--has been implicated as a cause of fundamental change to downstream aquatic ecosystems. Flow modification changes the patterns and functionality of the natural flow regime, and has the potential to restrict population connectivity and gene flow in river-dependent organisms. Since population connectivity and the maintenance of genetic diversity are fundamental drivers of long-term persistence, understanding the extent flow modification impacts these critical attributes of genetic health is an important goal for long-term conservation. Foothill yellow-legged frogs (Rana boylii) were historically abundant throughout many western rivers but have declined since the onset of regulation. However, the extent to which R. boylii populations in rivers with altered flow regimes are maintaining connectivity and genetic diversity is unknown. Here we use genetic methods to investigate the impacts of flow alteration on R. boylii to explore their potential for long-term persistence under continued flow modification. We found R. boylii in rivers with flow modification showed striking patterns of isolation and trajectories of genetic diversity loss relative to unregulated rivers. For example, flow modification explained the greatest amount of variance in population genetic differentiation compared with other covariates including geographic distance. Importantly, patterns of connectivity and genetic diversity loss were observed regardless of flow alteration level but were most prominent in locations with the greatest flow modification intensity. Although our results do not bode well for long-term persistence of R. boylii populations under current flow regulation regimes, they do highlight the power of genetic monitoring for assessing population health in aquatic organisms.

ecology↗