Transcriptomic analysis of cardiac gene expression across the life course in male and female mice.

Risk for heart disease increases with advanced age and differs between sexes, with females generally protected from heart disease until menopause. Despite these epidemiological observations, the molecular mechanisms that underlie sex-specific differences in cardiac function have not been fully described. We used high throughput transcriptomics in juvenile (5 weeks), adult (4-6 months), and aged (18 months) male and female mice to understand how cardiac gene expression changes across the life course and by sex. While male gene expression profiles differed between juvenile-adult and juvenile-aged (254 and 518 genes, respectively), we found no significant differences in adult-aged gene expression. Females had distinct gene expression changes across the life course with 1835 genes in juvenile-adult and 1328 in adult-aged. Analysis of differentially expressed genes (DEGs) suggests that juvenile to adulthood genes were clustered in cell cycle and development-related pathways in contrast to adulthood-aged which were characterized by immune-and inflammation-related pathways. Analysis of sex differences within each age suggests that juvenile and aged cardiac transcriptomes are different between males and females, with significantly fewer DEGs identified in adult males and females. Interestingly, the male-female differences in early age were distinct from those in advanced age. These findings are in contrast to expected sex differences historically attributed to estrogen and could not be explained by estrogen-direct mechanisms alone as evidenced by juvenile sexual immaturity and reproductive incompetence in the aged mice. Together, distinct trajectories in cardiac transcriptomic profiles highlight fundamental sex differences across the life course and demonstrate the need for the consideration of age and sex as biological variables in heart disease.

Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

Gradient Forests (GF) is a machine learning algorithm that is gaining in popularity for studying the environmental drivers of genomic variation and for incorporating genomic information into climate change impact assessments. Here we (i) provide the first experimental evaluation of the ability of "genomic offsets" - a metric of climate maladaptation derived from Gradient Forests - to predict organismal responses to environmental change, and (ii) explore the use of GF for identifying candidate SNPs. We used high-throughput sequencing, genome scans, and several methods, including GF, to identify candidate loci associated with climate adaptation in balsam poplar (Populus balsamifera L.). Individuals collected throughout balsam poplar's range also were planted in two common garden experiments. We used GF to relate candidate loci to environmental gradients and predict the expected magnitude of the response (i.e., the genetic offset metric of maladaptation) of populations when transplanted from their "home" environment to the common gardens. We then compared the predicted genetic offsets from different sets of candidate and randomly selected SNPs to measurements of population performance in the common gardens. We found the expected inverse relationship between genetic offset and performance: populations with larger predicted genetic offsets performed worse in the common gardens than populations with smaller offsets. Also, genetic offset better predicted performance than did "naive" climate transfer distances. However, sets of randomly selected SNPs predicted performance slightly better than did candidate SNPs. Our study provides evidence that genetic offsets represent a first order estimate of the degree of expected maladaptation of populations exposed to rapid environmental change and suggests GF may have some promise as a method for identifying candidate SNPs.

Cardiac response to adrenergic stress differs by sex and across the lifespan.

The aging heart is well-characterized by a diminished responsiveness to adrenergic activation. However, the precise mechanisms by which age and sex impact adrenergic-mediated cardiac function remain poorly described. In the current investigation, we compared the cardiac response to adrenergic stress to gain mechanistic understanding of how the response to an adrenergic challenge differs by sex and age. Juvenile (4 weeks), adult (4-6 months), and aged (18-20 months) male and female mice were treated with the ß-agonist isoproterenol (ISO) for 1 week. ISO-induced morphometric changes were age- and sex-dependent as juvenile and adult mice of both sexes had higher left ventricle weights while aged mice did not increase cardiac mass. Adults increased myocyte cell size and deposited fibrotic matrix in response to ISO, while juvenile and aged animals did not show evidence of hypertrophy or fibrosis. Juvenile females and adults underwent expected changes in systolic function with higher heart rate, ejection fraction, and fractional shortening. However, cardiac function in aged animals was not altered in response to ISO. Transcriptomic analysis identified significant differences in gene expression by age and sex, with few overlapping genes and pathways between groups. Fibrotic and adrenergic signaling pathways were upregulated in adult hearts. Juvenile hearts upregulated genes in the adrenergic pathway with few changes in fibrosis, while aged mice robustly upregulated fibrotic gene expression without changes in adrenergic genes. We suggest that the response to adrenergic stress significantly differs across the lifespan and by sex. Mechanistic definition of these age-related pathways by sex is critical for future research aimed at treating age-related cardiac adrenergic desensitization.

CRISPRcruncher: A tool for engineering restriction sites into coding regions.

CRISPR/Cas9 genome editing strategies often rely on the placement of an introduced restriction endonuclease (RE) site adjacent to the genomic edit of interest. This allows for rapid initial PCR-based detection of cells and organisms containing the edit of interest and may also be used for subsequent genotyping. Nevertheless, engineering RE sites at optimal locations within coding regions can be difficult due to the many hundreds of potential endonuclease options and the strict requirement to maintain the correct amino acid sequence. Here we report CRISPRcruncher, a computational tool that analyzes an input coding sequence and produces a complete list of all possible changes that could be made that will create new RE sites while preserving the original peptide sequence. Notably, for sequences tested, CRISPRcruncher identified approximately one new RE site per input nucleotide when mining for 4-bp or longer RE motifs and 0.5 new RE sites per input nucleotide when mining for 6-bp or longer motifs. Therefore, CRISPRcruncher represents a powerful new computational tool in the CRISPR arsenal.

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.

Influence of Range Position on Locally Adaptive Gene-Environment Associations in Populus Flowering Time Genes.

Local adaptation is pervasive in forest trees, which are characterized by large effective population sizes spanning broad climatic gradients. In addition to having relatively contiguous populations, many species also form isolated populations along the rear edge of their range. These rear-edge populations may contain unique adaptive diversity reflecting a history of selection in marginal environments. Thus, discovering genomic regions conferring local adaptation in rear edge populations is a key priority for landscape genomics to ensure conservation of genetic resources under climate change. Here, we report on adaptive gene-environment associations in single nucleotide polymorphisms (SNPs) from 27 genes in the Populus flowering time gene network, analyzed on a range-wide collection of >1000 balsam poplar trees, including dense sampling of the southern range edge. We use a combined approach of local adaptation scans to identify candidate SNPs, followed by modeling the compositional turnover of adaptive SNPs along multivariate climate gradients using gradient forests (GF). Flowering time candidate genes contained extensive evidence of climate adaptation, namely outlier population structure and gene-environment associations, along with allele frequency divergence between the core and edge of the range. GF showed strong allele frequency turnover along gradients of elevation and diurnal and temperature variability, as well as threshold responses to summer temperature and precipitation, with turnover especially strong in edge populations that occur at high elevation but southerly latitudes. We discuss these results in light of how climate may disrupt locally adaptive gene-environment relationships, and suggest that rear edge populations hold climate-adaptive variants that should be targeted for conservation.

StrAuto: automation and parallelization of STRUCTURE analysis.

BACKGROUND: Population structure inference using the software STRUCTURE has become an integral part of population genetic studies covering a broad spectrum of taxa including humans. The ever-expanding size of genetic data sets poses computational challenges for this analysis. Although at least one tool currently implements parallel computing to reduce computational overload of this analysis, it does not fully automate the use of replicate STRUCTURE analysis runs required for downstream inference of optimal K. There is pressing need for a tool that can deploy population structure analysis on high performance computing clusters. RESULTS: We present an updated version of the popular Python program StrAuto, to streamline population structure analysis using parallel computing. StrAuto implements a pipeline that combines STRUCTURE analysis with the Evanno Δ K analysis and visualization of results using STRUCTURE HARVESTER. Using benchmarking tests, we demonstrate that StrAuto significantly reduces the computational time needed to perform iterative STRUCTURE analysis by distributing runs over two or more processors. CONCLUSION: StrAuto is the first tool to integrate STRUCTURE analysis with post-processing using a pipeline approach in addition to implementing parallel computation - a set up ideal for deployment on computing clusters. StrAuto is distributed under the GNU GPL (General Public License) and available to download from http://strauto.popgen.org .

Hiding in Plain Sight: A Case for Cryptic Metapopulations in Brook Trout (Salvelinus fontinalis).

A fundamental issue in the management and conservation of biodiversity is how to define a population. Spatially contiguous fish occupying a stream network have often been considered to represent a single, homogenous population. However, they may also represent multiple discrete populations, a single population with genetic isolation-by-distance, or a metapopulation. We used microsatellite DNA and a large-scale mark-recapture study to assess population structure in a spatially contiguous sample of Brook Trout (Salvelinus fontinalis), a species of conservation concern. We found evidence for limited genetic exchange across small spatial scales and in the absence of barriers to physical movement. Mark-recapture and stationary passive integrated transponder antenna records demonstrated that fish from two tributaries very seldom moved into the opposite tributary, but movements between the tributaries and mainstem were more common. Using Bayesian genetic clustering, we identified two genetic groups that exhibited significantly different growth rates over three years of study, yet survival rates were very similar. Our study highlights the importance of considering the possibility of multiple genetically distinct populations occurring within spatially contiguous habitats, and suggests the existence of a cryptic metapopulation: a spatially continuous distribution of organisms exhibiting metapopulation-like behaviors.

A Consensus Genetic Map for Pinus taeda and Pinus elliottii and Extent of Linkage Disequilibrium in Two Genotype-Phenotype Discovery Populations of Pinus taeda.

A consensus genetic map for Pinus taeda (loblolly pine) and Pinus elliottii (slash pine) was constructed by merging three previously published P. taeda maps with a map from a pseudo-backcross between P. elliottii and P. taeda. The consensus map positioned 3856 markers via genotyping of 1251 individuals from four pedigrees. It is the densest linkage map for a conifer to date. Average marker spacing was 0.6 cM and total map length was 2305 cM. Functional predictions of mapped genes were improved by aligning expressed sequence tags used for marker discovery to full-length P. taeda transcripts. Alignments to the P. taeda genome mapped 3305 scaffold sequences onto 12 linkage groups. The consensus genetic map was used to compare the genome-wide linkage disequilibrium in a population of distantly related P. taeda individuals (ADEPT2) used for association genetic studies and a multiple-family pedigree used for genomic selection (CCLONES). The prevalence and extent of LD was greater in CCLONES as compared to ADEPT2; however, extended LD with LGs or between LGs was rare in both populations. The average squared correlations, r(2), between SNP alleles less than 1 cM apart were less than 0.05 in both populations and r(2) did not decay substantially with genetic distance. The consensus map and analysis of linkage disequilibrium establish a foundation for comparative association mapping and genomic selection in P. taeda and P. elliottii.

Genetic divergence and signatures of natural selection in marginal populations of a keystone, long-lived conifer, Eastern White Pine (Pinus strobus) from Northern Ontario.

Marginal populations are expected to provide the frontiers for adaptation, evolution and range shifts of plant species under the anticipated climate change conditions. Marginal populations are predicted to show genetic divergence from central populations due to their isolation, and divergent natural selection and genetic drift operating therein. Marginal populations are also expected to have lower genetic diversity and effective population size (Ne) and higher genetic differentiation than central populations. We tested these hypotheses using eastern white pine (Pinus strobus) as a model for keystone, long-lived widely-distributed plants. All 614 eastern white pine trees, in a complete census of two populations each of marginal old-growth, central old-growth, and central second-growth, were genotyped at 11 microsatellite loci. The central populations had significantly higher allelic and genotypic diversity, latent genetic potential (LGP) and Ne than the marginal populations. However, heterozygosity and fixation index were similar between them. The marginal populations were genetically diverged from the central populations. Model testing suggested predominant north to south gene flow in the study area with curtailed gene flow to northern marginal populations. Signatures of natural selection were detected at three loci in the marginal populations; two showing divergent selection with directional change in allele frequencies, and one balancing selection. Contrary to the general belief, no significant differences were observed in genetic diversity, differentiation, LGP, and Ne between old-growth and second-growth populations. Our study provides information on the dynamics of migration, genetic drift and selection in central versus marginal populations of a keystone long-lived plant species and has broad evolutionary, conservation and adaptation significance.

Isolation and characterization of nine microsatellite loci in an ant-tended treehopper Publilia concava.

Publilia concava is an eastern North American membracid commonly occurring in large but spatially patchy aggregations, primarily on the host plant Solidago altissima. Like other myrmecophiles, P. concava provides sugary excretions to ants in return for the various protective, competitive or even sanitary benefits that ants provide. We developed nine microsatellite loci from P. concava. Mean per locus allele number was 6.78, and observed heterozygosities ranged from 0.03 to 0.850. One locus exhibited significant heterozygote deficit, possibly due to the presence of null alleles. These markers provide important tools for future spatial ecological studies in this model system for the study of mutualism.

Kin structure provides no explanation for intruders in social aphids.

Nontraditional social organisms have received increasing attention in recent years, because they present opportunities to study the convergent properties of social evolution. Some aphid species are social, occurring in dense clones with specialized morphs that attack predators and parasites. Little is known about how social aphid colonies resolve conflicts of interest when clonal barriers break down. Pemphigus obesinymphae is a North American gall-forming social aphid that produces both nymphal defenders that protect natal clones, and specialized intruders that invade other nearby clones on their host plants. We tested the hypothesis that clones are arranged on their host plants in spatial clusters of related family groups, such that intruders would be biased towards movement within kin groups. Movement within and not between kin groups would then provide insight into the nature of conflict in this social aphid. We sampled eight sites in the eastern United States and in Arizona, and used eight microsatellite markers to estimate pairwise relatedness between spatial groups. We found little evidence of deviation from random distributions of genotypes on their host plants. Evidently, Pem. obesinymphae intruders typically exploit unrelated clones, and spatial orientation provides no solution to the problem of 'polyclonality' in this species. We discuss implications of this result for our understanding of cooperation and conflict in social aphids.