Transcriptome-wide gene-gene interaction associations elucidate pathways and functional enrichment of complex traits.

It remains unknown to what extent gene-gene interactions contribute to complex traits. Here, we introduce a new approach using predicted gene expression to perform exhaustive transcriptome-wide interaction studies (TWISs) for multiple traits across all pairs of genes expressed in several tissue types. Using imputed transcriptomes, we simultaneously reduce the computational challenge and improve interpretability and statistical power. We discover (in the UK Biobank) and replicate (in independent cohorts) several interaction associations, and find several hub genes with numerous interactions. We also demonstrate that TWIS can identify novel associated genes because genes with many or strong interactions have smaller single-locus model effect sizes. Finally, we develop a method to test gene set enrichment of TWIS associations (E-TWIS), finding numerous pathways and networks enriched in interaction associations. Epistasis is may be widespread, and our procedure represents a tractable framework for beginning to explore gene interactions and identify novel genomic targets.

Disentangling differing relationships between internalizing disorders and alcohol use.

Both internalizing disorders and alcohol use have dramatic, wide-spread implications for global health. Previous work has established common phenotypic comorbidity among these disorders, as well as shared genetic variation underlying them both. We used genomic structural equation modeling to investigate the shared genetics of internalizing, externalizing, and alcohol use traits, as well as to explore whether specific domains of internalizing symptoms mediate the contrasting relationships with problematic alcohol use compared to alcohol consumption. We also examined patterns of genetic correlations between similar traits within additional Finnish and East Asian ancestry groups. When the shared genetic influence of externalizing psychopathology was accounted for, the genetic effect of internalizing traits on alcohol use was reduced, suggesting the important role of common genetic factors underlying multiple psychiatric disorders and their genetic influences on comorbidity of internalizing and alcohol use traits. Individual internalizing domains had contrasting effects on frequency of alcohol consumption, which demonstrate the complex system of pleiotropy that exists, even within similar disorders, and can be missed when evaluating only relationships among formal diagnoses. Future work must consider the broad effects of shared psychopathology along with the fine-scale effects of heterogeneity within disorders to more fully understand the biology underlying complex traits.

Testing Association of Previously Implicated Gene Sets and Gene-Networks in Nicotine Exposed Mouse Models with Human Smoking Phenotypes.

INTRODUCTION: Smoking behaviors are partly heritable, yet the genetic and environmental mechanisms underlying smoking phenotypes are not fully understood. Developmental nicotine exposure (DNE) is a significant risk factor for smoking and leads to gene expression changes in mouse models; however, it is unknown whether the same genes whose expression is impacted by DNE are also those underlying smoking genetic liability. We examined whether genes whose expression in D1-type striatal medium spiny neurons due to DNE in the mouse are also associated with human smoking behaviors. METHODS: Specifically, we assessed whether human orthologs of mouse-identified genes, either individually or as a set, were genetically associated with five human smoking traits using MAGMA and S-LDSC while implementing a novel expression-based gene-SNP annotation methodology. RESULTS: We found no strong evidence that these genes sets were more strongly associated with smoking behaviors than the rest of the genome, but ten of these individual genes were significantly associated with three of the five human smoking traits examined (p < 2.5e-6). Three of these genes have not been reported previously and were discovered only when implementing the expression-based annotation. CONCLUSIONS: These results suggest the genes whose expression is impacted by DNE in mice are largely distinct from those contributing to smoking genetic liability in humans. However, examining a single mouse neuronal cell type may be too fine a resolution for comparison, suggesting that experimental manipulation of nicotine consumption, reward, or withdrawal in mice may better capture genes related to the complex genetics of human tobacco use. IMPLICATIONS: Genes whose expression is impacted by DNE in mouse D1-type striatal medium spiny neurons were not found to be, as a whole, more strongly associated with human smoking behaviors than the rest of the genome, though ten individual mouse-identified genes were associated with human smoking traits. This suggests little overlap between the genetic mechanisms impacted by DNE and those influencing heritable liability to smoking phenotypes in humans. Further research is warranted to characterize how developmental nicotine exposure paradigms in mice can be translated to understand nicotine use in humans and their heritable effects on smoking.

A 5-Enolpyruvylshikimate 3-Phosphate Synthase Functions as a Transcriptional Repressor in Populus.

Long-lived perennial plants, with distinctive habits of inter-annual growth, defense, and physiology, are of great economic and ecological importance. However, some biological mechanisms resulting from genome duplication and functional divergence of genes in these systems remain poorly studied. Here, we discovered an association between a poplar (Populus trichocarpa) 5-enolpyruvylshikimate 3-phosphate synthase gene (PtrEPSP) and lignin biosynthesis. Functional characterization of PtrEPSP revealed that this isoform possesses a helix-turn-helix motif in the N terminus and can function as a transcriptional repressor that regulates expression of genes in the phenylpropanoid pathway in addition to performing its canonical biosynthesis function in the shikimate pathway. We demonstrated that this isoform can localize in the nucleus and specifically binds to the promoter and represses the expression of a SLEEPER-like transcriptional regulator, which itself specifically binds to the promoter and represses the expression of PtrMYB021 (known as MYB46 in Arabidopsis thaliana), a master regulator of the phenylpropanoid pathway and lignin biosynthesis. Analyses of overexpression and RNAi lines targeting PtrEPSP confirmed the predicted changes in PtrMYB021 expression patterns. These results demonstrate that PtrEPSP in its regulatory form and PtrhAT form a transcriptional hierarchy regulating phenylpropanoid pathway and lignin biosynthesis in Populus.

Whole-Genome Sequencing of Inbred Mouse Strains Selected for High and Low Open-Field Activity.

We conducted whole-genome sequencing of four inbred mouse strains initially selected for high (H1, H2) or low (L1, L2) open-field activity (OFA), and then examined strain distribution patterns for all DNA variants that differed between their BALB/cJ and C57BL/6J parental strains. Next, we assessed genome-wide sharing (3,678,826 variants) both between and within the High and Low Activity strains. Results suggested that about 10% of these DNA variants may be associated with OFA, and clearly demonstrated its polygenic nature. Finally, we conducted bioinformatic analyses of functional genomics data from mouse, rat, and human to refine previously identified quantitative trait loci (QTL) for anxiety-related measures. This combination of sequence analysis and genomic-data integration facilitated refinement of previously intractable QTL findings, and identified possible genes for functional follow-up studies.

Genetic data improves niche model discrimination and alters the direction and magnitude of climate change forecasts.

Ecological niche models (ENMs) have classically operated under the simplifying assumptions that there are no barriers to gene flow, species are genetically homogeneous (i.e., no population-specific local adaptation), and all individuals share the same niche. Yet, these assumptions are violated for most broadly distributed species. Here, we incorporate genetic data from the widespread riparian tree species narrowleaf cottonwood (Populus angustifolia) to examine whether including intraspecific genetic variation can alter model performance and predictions of climate change impacts. We found that (1) P. angustifolia is differentiated into six genetic groups across its range from México to Canada and (2) different populations occupy distinct climate niches representing unique ecotypes. Comparing model discriminatory power, (3) all genetically informed ecological niche models (gENMs) outperformed the standard species-level ENM (3-14% increase in AUC; 1-23% increase in pROC). Furthermore, (4) gENMs predicted large differences among ecotypes in both the direction and magnitude of responses to climate change and (5) revealed evidence of niche divergence, particularly for the Eastern Rocky Mountain ecotype. (6) Models also predicted progressively increasing fragmentation and decreasing overlap between ecotypes. Contact zones are often hotspots of diversity that are critical for supporting species' capacity to respond to present and future climate change, thus predicted reductions in connectivity among ecotypes is of conservation concern. We further examined the generality of our findings by comparing our model developed for a higher elevation Rocky Mountain species with a related desert riparian cottonwood, P. fremontii. Together our results suggest that incorporating intraspecific genetic information can improve model performance by addressing this important source of variance. gENMs bring an evolutionary perspective to niche modeling and provide a truly "adaptive management" approach to support conservation genetic management of species facing global change.

Little Evidence of Modified Genetic Effect of rs16969968 on Heavy Smoking Based on Age of Onset of Smoking.

INTRODUCTION: Tobacco smoking is the leading cause of preventable death globally. Smoking quantity, measured in cigarettes per day, is influenced both by the age of onset of regular smoking (AOS) and by genetic factors, including a strong effect of the nonsynonymous single-nucleotide polymorphism rs16969968. A previous study by Hartz et al. reported an interaction between these two factors, whereby rs16969968 risk allele carriers who started smoking earlier showed increased risk for heavy smoking compared with those who started later. This finding has yet to be replicated in a large, independent sample. METHODS: We performed a preregistered, direct replication attempt of the rs16969968 × AOS interaction on smoking quantity in 128 383 unrelated individuals from the UK Biobank, meta-analyzed across ancestry groups. We fit statistical association models mirroring the original publication as well as formal interaction tests on multiple phenotypic and analytical scales. RESULTS: We replicated the main effects of rs16969968 and AOS on cigarettes per day but failed to replicate the interaction using previous methods. Nominal significance of the rs16969968 × AOS interaction term depended strongly on the scale of analysis and the particular phenotype, as did associations stratified by early/late AOS. No interaction tests passed genome-wide correction (α = 5e-8), and all estimated interaction effect sizes were much smaller in magnitude than previous estimates. CONCLUSIONS: We failed to replicate the strong rs16969968 × AOS interaction effect previously reported. If such gene-moderator interactions influence complex traits, they likely depend on scale of measurement, and current biobanks lack the power to detect significant genome-wide associations given the minute effect sizes expected. IMPLICATIONS: We failed to replicate the strong rs16969968 × AOS interaction effect on smoking quantity previously reported. If such gene-moderator interactions influence complex traits, current biobanks lack the power to detect significant genome-wide associations given the minute effect sizes expected. Furthermore, many potential interaction effects are likely to depend on the scale of measurement employed.

Relationships between estimated autozygosity and complex traits in the UK Biobank.

Inbreeding increases the risk of certain Mendelian disorders in humans but may also reduce fitness through its effects on complex traits and diseases. Such inbreeding depression is thought to occur due to increased homozygosity at causal variants that are recessive with respect to fitness. Until recently it has been difficult to amass large enough sample sizes to investigate the effects of inbreeding depression on complex traits using genome-wide single nucleotide polymorphism (SNP) data in population-based samples. Further, it is difficult to infer causation in analyses that relate degree of inbreeding to complex traits because confounding variables (e.g., education) may influence both the likelihood for parents to outbreed and offspring trait values. The present study used runs of homozygosity in genome-wide SNP data in up to 400,000 individuals in the UK Biobank to estimate the proportion of the autosome that exists in autozygous tracts-stretches of the genome which are identical due to a shared common ancestor. After multiple testing corrections and controlling for possible sociodemographic confounders, we found significant relationships in the predicted direction between estimated autozygosity and three of the 26 traits we investigated: age at first sexual intercourse, fluid intelligence, and forced expiratory volume in 1 second. Our findings corroborate those of several published studies. These results may imply that these traits have been associated with Darwinian fitness over evolutionary time. However, some of the autozygosity-trait relationships were attenuated after controlling for background sociodemographic characteristics, suggesting that alternative explanations for these associations have not been eliminated. Care needs to be taken in the design and interpretation of ROH studies in order to glean reliable information about the genetic architecture and evolutionary history of complex traits.

Novel characterization of the multivariate genetic architecture of internalizing psychopathology and alcohol use.

Genetic correlations suggest that the genetic relationship of alcohol use with internalizing psychopathology depends on the measure of alcohol use. Problematic alcohol use (PAU) is positively genetically correlated with internalizing psychopathology, whereas alcohol consumption ranges from not significantly correlated to moderately negatively correlated with internalizing psychopathology. To explore these different genetic relationships of internalizing psychopathology with alcohol use, we performed a multivariate genome-wide association study of four correlated factors (internalizing psychopathology, PAU, quantity of alcohol consumption, and frequency of alcohol consumption) and then assessed genome-wide and local genetic covariance between these factors. We identified 14 significant regions of local, largely positive, genetic covariance between PAU and internalizing psychopathology and 12 regions of significant local genetic covariance (including both positive and negative genetic covariance) between consumption factors and internalizing psychopathology. Partitioned genetic covariance among functional annotations suggested that brain tissues contribute significantly to positive genetic covariance between internalizing psychopathology and PAU but not to the genetic covariance between internalizing psychopathology and quantity or frequency of alcohol consumption. We hypothesize that genome-wide genetic correlations between alcohol use and psychiatric traits may not capture the more complex shared or divergent genetic architectures at the locus or tissue specific level. This study highlights the complexity of genetic architectures of alcohol use and internalizing psychopathology, and the differing shared genetics of internalizing disorders with PAU compared to consumption.

The Role of A Priori-Identified Addiction and Smoking Gene Sets in Smoking Behaviors.

INTRODUCTION: Smoking is a leading cause of death, and genetic variation contributes to smoking behaviors. Identifying genes and sets of genes that contribute to risk for addiction is necessary to prioritize targets for functional characterization and for personalized medicine. METHODS: We performed a gene set-based association and heritable enrichment study of two addiction-related gene sets, those on the Smokescreen Genotyping Array and the nicotinic acetylcholine receptors, using the largest available GWAS summary statistics. We assessed smoking initiation, cigarettes per day, smoking cessation, and age of smoking initiation. RESULTS: Individual genes within each gene set were significantly associated with smoking behaviors. Both sets of genes were significantly associated with cigarettes per day, smoking initiation, and smoking cessation. Age of initiation was only associated with the Smokescreen gene set. Although both sets of genes were enriched for trait heritability, each accounts for only a small proportion of the single nucleotide polymorphism-based heritability (2%-12%). CONCLUSIONS: These two gene sets are associated with smoking behaviors, but collectively account for a limited amount of the genetic and phenotypic variation of these complex traits, consistent with high polygenicity. IMPLICATIONS: We evaluated evidence for the association and heritable contribution of expert-curated and bioinformatically identified sets of genes related to smoking. Although they impact smoking behaviors, these specifically targeted genes do not account for much of the heritability in smoking and will be of limited use for predictive purposes. Advanced genome-wide approaches and integration of other 'omics data will be needed to fully account for the genetic variation in smoking phenotypes.

Multitrait genome-wide association analysis of Populus trichocarpa identifies key polymorphisms controlling morphological and physiological traits.

Genome-wide association studies (GWAS) have great promise for identifying the loci that contribute to adaptive variation, but the complex genetic architecture of many quantitative traits presents a substantial challenge. We measured 14 morphological and physiological traits and identified single nucleotide polymorphism (SNP)-phenotype associations in a Populus trichocarpa population distributed from California, USA to British Columbia, Canada. We used whole-genome resequencing data of 882 trees with more than 6.78 million SNPs, coupled with multitrait association to detect polymorphisms with potentially pleiotropic effects. Candidate genes were validated with functional data. Broad-sense heritability (H2 ) ranged from 0.30 to 0.56 for morphological traits and 0.08 to 0.36 for physiological traits. In total, 4 and 20 gene models were detected using the single-trait and multitrait association methods, respectively. Several of these associations were corroborated by additional lines of evidence, including co-expression networks, metabolite analyses, and direct confirmation of gene function through RNAi. Multitrait association identified many more significant associations than single-trait association, potentially revealing pleiotropic effects of individual genes. This approach can be particularly useful for challenging physiological traits such as water-use efficiency or complex traits such as leaf morphology, for which we were able to identify credible candidate genes by combining multitrait association with gene co-expression and co-methylation data.

Characterization of a large sex determination region in Salix purpurea L. (Salicaceae).

Dioecy has evolved numerous times in plants, but heteromorphic sex chromosomes are apparently rare. Sex determination has been studied in multiple Salix and Populus (Salicaceae) species, and P. trichocarpa has an XY sex determination system on chromosome 19, while S. suchowensis and S. viminalis have a ZW system on chromosome 15. Here we use whole genome sequencing coupled with quantitative trait locus mapping and a genome-wide association study to characterize the genomic composition of the non-recombining portion of the sex determination region. We demonstrate that Salix purpurea also has a ZW system on chromosome 15. The sex determination region has reduced recombination, high structural polymorphism, an abundance of transposable elements, and contains genes that are involved in sex expression in other plants. We also show that chromosome 19 contains sex-associated markers in this S. purpurea assembly, along with other autosomes. This raises the intriguing possibility of a translocation of the sex determination region within the Salicaceae lineage, suggesting a common evolutionary origin of the Populus and Salix sex determination loci.

Adaptive introgression and maintenance of a trispecies hybrid complex in range-edge populations of Populus.

In hybrid zones occurring in marginal environments, adaptive introgression from one species into the genomic background of another may constitute a mechanism facilitating adaptation at range limits. Although recent studies have improved our understanding of adaptive introgression in widely distributed tree species, little is known about the dynamics of this process in populations at the margins of species ranges. We investigated the extent of introgression between three species of the genus Populus sect. Tacamahaca (P. balsamifera, P. angustifolia and P. trichocarpa) at the margins of their distributions in the Rocky Mountain region of the United States and Canada. Using genotyping by sequencing (GBS), we analysed ~ 83,000 single nucleotide polymorphisms genotyped in 296 individuals from 29 allopatric and sympatric populations of the three species. We found a trispecies hybrid complex present throughout the zone of range overlap, including early as well as advanced generation backcross hybrids, indicating recurrent gene flow in this hybrid complex. Using genomic cline analysis, we found evidence of non-neutral patterns of introgression at 23% of loci in hybrids, of which 47% and 8% represented excess ancestry from P. angustifolia and P. balsamifera, respectively. Gene ontology analysis suggested these genomic regions were enriched for genes associated with photoperiodic regulation, metal ion transport, maintenance of redox homeostasis and cell wall metabolites involved in regulation of seasonal dormancy. Our study demonstrates the role of adaptive introgression in a multispecies hybrid complex in range-edge populations and has implications for understanding the evolutionary dynamics of adaptation in hybrid zones, especially at the margins of species distributions.

Narrow-sense heritability estimation of complex traits using identity-by-descent information.

Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while possibly avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole-genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). In simulations, the IBD-based approach produced unbiased heritability estimates, even when CVs were extremely rare, although precision was low. However, population stratification and non-genetic familial environmental effects shared across generations led to strong biases in IBD-based heritability. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in these real data, suggesting that more work may be required to understand and mitigate factors that influence IBD-based heritability estimates.

Conserving threatened riparian ecosystems in the American West: Precipitation gradients and river networks drive genetic connectivity and diversity in a foundation riparian tree (Populus angustifolia).

Gene flow is an evolutionary process that supports genetic connectivity and contributes to the capacity of species to adapt to environmental change. Yet, for most species, little is known about the specific environmental factors that influence genetic connectivity, or their effects on genetic diversity and differentiation. We used a landscape genetic approach to understand how geography and climate influence genetic connectivity in a foundation riparian tree (Populus angustifolia), and their relationships with specieswide patterns of genetic diversity and differentiation. Using multivariate restricted optimization in a reciprocal causal modelling framework, we quantified the relative contributions of riparian network connectivity, terrestrial upland resistance and climate gradients on genetic connectivity. We found that (i) all riparian corridors, regardless of river order, equally facilitated connectivity, while terrestrial uplands provided 2.5× more resistance to gene flow than riparian corridors. (ii) Cumulative differences in precipitation seasonality and precipitation of the warmest quarter were the primary climatic factors driving genetic differentiation; furthermore, maximum climate resistance was 45× greater than riparian resistance. (iii) Genetic diversity was positively correlated with connectivity (R2  = 0.3744, p = .0019), illustrating the utility of resistance models for identifying landscape conditions that can support a species' ability to adapt to environmental change. From these results, we present a map highlighting key genetic connectivity corridors across P. angustifolia's range that if disrupted could have long-term ecological and evolutionary consequences. Our findings provide recommendations for conservation and restoration management of threatened riparian ecosystems throughout the western USA and the high biodiversity they support.

Phenotypic and Genetic Relationship Between BMI and Drinking in a Sample of UK Adults.

The health impairments derived from both alcoholism and obesity are well known. However, reports that relate increased alcohol use with increased measures of obesity have been mixed in their findings, especially with respect to genetic factors that could potentially link these two behaviors. Here, using a large sample of adults from the UK (n ≈ 113,000), we report both the observed and genetic correlations between BMI (kg/m2) and two measures of alcohol use: reported quantity (drinks per week) and frequency of use (from never to daily). Overall, both observationally and genetically, alcohol intake is negatively correlated with BMI. Phenotypic correlations ranged from -0.01 to -0.17, and genetic correlations ranged from -0.1 to -0.4. Genetic correlations tended to be stronger than the phenotypic correlations, and these correlations were stronger in females and between BMI and, specifically, frequency of use. Though the mechanisms driving these relationships are yet to be identified, we can conclude that the genetic factors related to drinking both more and more often are shared with those responsible for lower BMI.

High-resolution genetic mapping of allelic variants associated with cell wall chemistry in Populus.

BACKGROUND: QTL cloning for the discovery of genes underlying polygenic traits has historically been cumbersome in long-lived perennial plants like Populus. Linkage disequilibrium-based association mapping has been proposed as a cloning tool, and recent advances in high-throughput genotyping and whole-genome resequencing enable marker saturation to levels sufficient for association mapping with no a priori candidate gene selection. Here, multiyear and multienvironment evaluation of cell wall phenotypes was conducted in an interspecific P. trichocarpa x P. deltoides pseudo-backcross mapping pedigree and two partially overlapping populations of unrelated P. trichocarpa genotypes using pyrolysis molecular beam mass spectrometry, saccharification, and/ or traditional wet chemistry. QTL mapping was conducted using a high-density genetic map with 3,568 SNP markers. As a fine-mapping approach, chromosome-wide association mapping targeting a QTL hot-spot on linkage group XIV was performed in the two P. trichocarpa populations. Both populations were genotyped using the 34 K Populus Infinium SNP array and whole-genome resequencing of one of the populations facilitated marker-saturation of candidate intervals for gene identification. RESULTS: Five QTLs ranging in size from 0.6 to 1.8 Mb were mapped on linkage group XIV for lignin content, syringyl to guaiacyl (S/G) ratio, 5- and 6-carbon sugars using the mapping pedigree. Six candidate loci exhibiting significant associations with phenotypes were identified within QTL intervals. These associations were reproducible across multiple environments, two independent genotyping platforms, and different plant growth stages. cDNA sequencing for allelic variants of three of the six loci identified polymorphisms leading to variable length poly glutamine (PolyQ) stretch in a transcription factor annotated as an ANGUSTIFOLIA C-terminus Binding Protein (CtBP) and premature stop codons in a KANADI transcription factor as well as a protein kinase. Results from protoplast transient expression assays suggested that each of the polymorphisms conferred allelic differences in the activation of cellulose, hemicelluloses, and lignin pathway marker genes. CONCLUSION: This study illustrates the utility of complementary QTL and association mapping as tools for gene discovery with no a priori candidate gene selection. This proof of concept in a perennial organism opens up opportunities for discovery of novel genetic determinants of economically important but complex traits in plants.

Landscape genetic connectivity in a riparian foundation tree is jointly driven by climatic gradients and river networks.

Fremont cottonwood (Populus fremonti) is a foundation riparian tree species that drives community structure and ecosystem processes in southwestern U.S. ecosystems. Despite its ecological importance, little is known about the ecological and environmental processes that shape its genetic diversity, structure, and landscape connectivity. Here, we combined molecular analyses of 82 populations including 1312 individual trees dispersed over the species' geographical distribution. We reduced the data set to 40 populations and 743 individuals to eliminate admixture with a sibling species, and used multivariate restricted optimization and reciprocal causal modeling to evaluate the effects of river network connectivity and climatic gradients on gene flow. Our results confirmed the following: First, gene flow of Fremont cottonwood is jointly controlled by the connectivity of the river network and gradients of seasonal precipitation. Second, gene flow is facilitated by mid-sized to large rivers, and is resisted by small streams and terrestrial uplands, with resistance to gene flow decreasing with river size. Third, genetic differentiation increases with cumulative differences in winter and spring precipitation. Our results suggest that ongoing fragmentation of riparian habitats will lead to a loss of landscape-level genetic connectivity, leading to increased inbreeding and the concomitant loss of genetic diversity in a foundation species. These genetic effects will cascade to a much larger community of organisms, some of which are threatened and endangered.