Allele frequency dynamics under sex-biased demography and sex-specific inheritance in a pedigreed jay population.

Sex-biased demography, including sex-biased survival or migration, can alter allele frequency changes across the genome. In particular, we can expect different patterns of genetic variation on autosomes and sex chromosomes due to sex-specific differences in life histories, as well as differences in effective population size, transmission modes, and the strength and mode of selection. Here, we demonstrate the role that sex differences in life history played in shaping short-term evolutionary dynamics across the genome. We used a 25-year pedigree and genomic dataset from a long-studied population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of sex-biased demography and inheritance in shaping genome-wide allele frequency trajectories. We used gene dropping simulations to estimate individual genetic contributions to future generations and to model drift and immigration on the known pedigree. We quantified differential expected genetic contributions of males and females over time, showing the impact of sex-biased dispersal in a monogamous system. Due to female-biased dispersal, more autosomal variation is introduced by female immigrants. However, due to male-biased transmission, more Z variation is introduced by male immigrants. Finally, we partitioned the proportion of variance in allele frequency change through time due to male and female contributions. Overall, most allele frequency change is due to variance in survival and births. Males and females make similar contributions to autosomal allele frequency change, but males make higher contributions to allele frequency change on the Z chromosome. Our work shows the importance of understanding sex-specific demographic processes in characterizing genome-wide allele frequency change in wild populations.

Impacts of increasing isolation and environmental variation on Florida Scrub-Jay demography.

Isolation caused by anthropogenic habitat fragmentation can destabilize populations. Populations relying on the inflow of immigrants can face reduced fitness due to inbreeding depression as fewer new individuals arrive. Empirical studies of the demographic consequences of isolation are critical to understand how populations persist through changing conditions. We used a 34-year demographic and environmental dataset from a population of cooperatively-breeding Florida Scrub-Jays ( Aphelocoma coerulescens ) to create mechanistic models linking environmental and demographic factors to population growth rates. We found that the population has not declined despite both declining immigration and increasing inbreeding, owing to a coinciding response in breeder survival. We find evidence of density-dependent immigration, breeder survival, and fecundity, indicating that interactions between vital rates and local density play a role in buffering the population against change. Our study elucidates the impacts of isolation on demography and how long-term stability is maintained via demographic responses.

Dynamics of reduced genetic diversity in increasingly fragmented populations of Florida scrub jays,Aphelocoma coerulescens.

Understanding the genomic consequences of population decline is important for predicting species' vulnerability to intensifying global change. Empirical information about genomic changes in populations in the early stages of decline, especially for those still experiencing immigration, remains scarce. We used 7834 autosomal SNPs and demographic data for 288 Florida scrub jays (Aphelocoma coerulescens; FSJ) sampled in 2000 and 2008 to compare levels of genetic diversity, inbreeding, relatedness, and lengths of runs of homozygosity (ROH) between two subpopulations within dispersal distance of one another but have experienced contrasting demographic trajectories. At Archbold Biological Station (ABS), the FSJ population has been stable because of consistent habitat protection and management, while at nearby Placid Lakes Estates (PLE), the population declined precipitously due to suburban development. By the onset of our sampling in 2000, birds in PLE were already less heterozygous, more inbred, and on average more related than birds in ABS. No significant changes occurred in heterozygosity or inbreeding across the 8-year sampling interval, but average relatedness among individuals decreased in PLE, thus by 2008 average relatedness did not differ between sites. PLE harbored a similar proportion of short ROH but a greater proportion of long ROH than ABS, suggesting one continuous population of shared demographic history in the past, which is now experiencing more recent inbreeding. These results broadly uphold the predictions of simple population genetic models based on inferred effective population sizes and rates of immigration. Our study highlights how, in just a few generations, formerly continuous populations can diverge in heterozygosity and levels of inbreeding with severe local population decline despite ongoing gene flow.

Genome Diversity and the Origin of the Arabian Horse.

The Arabian horse, one of the world's oldest breeds of any domesticated animal, is characterized by natural beauty, graceful movement, athletic endurance, and, as a result of its development in the arid Middle East, the ability to thrive in a hot, dry environment. Here we studied 378 Arabian horses from 12 countries using equine single nucleotide polymorphism (SNP) arrays and whole-genome re-sequencing to examine hypotheses about genomic diversity, population structure, and the relationship of the Arabian to other horse breeds. We identified a high degree of genetic variation and complex ancestry in Arabian horses from the Middle East region. Also, contrary to popular belief, we could detect no significant genomic contribution of the Arabian breed to the Thoroughbred racehorse, including Y chromosome ancestry. However, we found strong evidence for recent interbreeding of Thoroughbreds with Arabians used for flat-racing competitions. Genetic signatures suggestive of selective sweeps across the Arabian breed contain candidate genes for combating oxidative damage during exercise, and within the "Straight Egyptian" subgroup, for facial morphology. Overall, our data support an origin of the Arabian horse in the Middle East, no evidence for reduced global genetic diversity across the breed, and unique genetic adaptations for both physiology and conformation.

Allele frequency dynamics in a pedigreed natural population.

A central goal of population genetics is to understand how genetic drift, natural selection, and gene flow shape allele frequencies through time. However, the actual processes underlying these changes-variation in individual survival, reproductive success, and movement-are often difficult to quantify. Fully understanding these processes requires the population pedigree, the set of relationships among all individuals in the population through time. Here, we use extensive pedigree and genomic information from a long-studied natural population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of different evolutionary processes in shaping patterns of genetic variation through time. We performed gene dropping simulations to estimate individual genetic contributions to the population and model drift on the known pedigree. We found that observed allele frequency changes are generally well predicted by accounting for the different genetic contributions of founders. Our results show that the genetic contribution of recent immigrants is substantial, with some large allele frequency shifts that otherwise may have been attributed to selection actually due to gene flow. We identified a few SNPs under directional short-term selection after appropriately accounting for gene flow. Using models that account for changes in population size, we partitioned the proportion of variance in allele frequency change through time. Observed allele frequency changes are primarily due to variation in survival and reproductive success, with gene flow making a smaller contribution. This study provides one of the most complete descriptions of short-term evolutionary change in allele frequencies in a natural population to date.

Genetic Diversity of Persian Arabian Horses and Their Relationship to Other Native Iranian Horse Breeds.

The principal aims of this study were to explore genetic diversity and genome-wide selection signatures in Persian Arabian horses and to determine genetic relationship of Persian Arabians with other Iranian horse breeds. We evaluated 71 horses from 8 matrilineal strains tracing to 47 mares from the mid to late 19th century, using the equine 670k single nucleotide polymorphism (SNP) BeadChip. Mean observed and expected heterozygosity were (0.43) and (0.45), respectively, average inbreeding measures (inbreeding estimates based on runs of homozygosity and pedigree information) were low, indicating high genetic diversity in Persian Arabian horses. Analysis of population genetic structure using STRUCTURE and principal component analysis suggested that Persian Arabian horses can be divided into 3 groups, however the groups do not match traditional matrilineal strains. In total, 15 genomic regions were identified by at least 2 of the 3 implemented methods, Tajima's D, H, and H12, as potentially under selection in Persian Arabian horses. Most of these peaks were found on chromosome 9, overlapping with QTLs previously associated with horse temperament. Biological function analysis of identified candidate genes highlighted enrichment of GO term "response to lipopolysaccharide" and KEGG pathway "chemokine-mediated signaling pathway," which are associated with immune responses and may have been targets of selection in Persian Arabian horses. Independent analyses of SNP data from 30 horses of 4 other Iranian breeds suggested distinct population structure between Persian Arabian, and Turkemen and Caspian horse breeds. Overall, the results of this study suggest a rich genetic diversity in the Persian Arabian horses and a clear genetic differentiation with Turkemen and Caspian breeds.

Genomic Consequences of Population Decline in the Endangered Florida Scrub-Jay.

Understanding the population genetic consequences of declining population size is important for conserving the many species worldwide facing severe decline [1]. Thorough empirical studies on the impacts of population reduction at a genome-wide scale in the wild are scarce because they demand huge field and laboratory investments [1, 2]. Previous studies have demonstrated the importance of gene flow in introducing genetic variation to small populations [3], but few have documented both genetic and fitness consequences of decreased immigration through time in a natural population [4-6]. Here we assess temporal variation in gene flow, inbreeding, and fitness using longitudinal genomic, demographic, and phenotypic data from a long-studied population of federally Threatened Florida scrub-jays (Aphelocoma coerulescens). We exhaustively sampled and genotyped the study population over two decades, providing one of the most detailed longitudinal investigations of genetics in a wild animal population to date. Immigrants were less heterozygous than residents but still introduced genetic variation into our study population. Owing to regional population declines, immigration into the study population declined from 1995-2013, resulting in increased levels of inbreeding and reduced fitness via inbreeding depression, even as the population remained demographically stable. Our results show that, contrary to conventional wisdom, small peripheral populations that already have undergone a genetic bottleneck may play a vital role in preserving genetic diversity of larger and seemingly stable populations. These findings underscore the importance of investing in the persistence of small populations and maintaining population connectivity in conservation of fragmented species.

Identifying the determinants of response to MDM2 inhibition.

Previous reports have provided evidence that p53 mutation is a strong negative predictor of response to MDM2 inhibitors. However, this correlation is not absolute, as many p53Mutant cell lines have been reported to respond to MDM2 inhibition, while many p53WT cell lines have been shown not to respond. To better understand the nature of these exceptions, we screened a panel of 260 cell lines and noted similar discrepancies. However, upon extensive curation of this panel, these apparent exceptions could be eliminated, revealing a perfect correlation between p53 mutational status and MDM2 inhibitor responsiveness. It has been suggested that the MDM2-amplified subset of p53WT tumors might be particularly sensitive to MDM2 inhibition. To facilitate clinical testing of this hypothesis, we identified a rationally derived copy number cutoff for assignment of functionally relevant MDM2 amplification. Applying this cutoff resulted in a pan-cancer MDM2 amplification rate far lower than previously published.

On the choice and number of microarrays for transcriptional regulatory network inference.

BACKGROUND: Transcriptional regulatory network inference (TRNI) from large compendia of DNA microarrays has become a fundamental approach for discovering transcription factor (TF)-gene interactions at the genome-wide level. In correlation-based TRNI, network edges can in principle be evaluated using standard statistical tests. However, while such tests nominally assume independent microarray experiments, we expect dependency between the experiments in microarray compendia, due to both project-specific factors (e.g., microarray preparation, environmental effects) in the multi-project compendium setting and effective dependency induced by gene-gene correlations. Herein, we characterize the nature of dependency in an Escherichia coli microarray compendium and explore its consequences on the problem of determining which and how many arrays to use in correlation-based TRNI. RESULTS: We present evidence of substantial effective dependency among microarrays in this compendium, and characterize that dependency with respect to experimental condition factors. We then introduce a measure neff of the effective number of experiments in a compendium, and find that corresponding to the dependency observed in this particular compendium there is a huge reduction in effective sample size i.e., neff = 14.7 versus n = 376. Furthermore, we found that the neff of select subsets of experiments actually exceeded neff of the full compendium, suggesting that the adage 'less is more' applies here. Consistent with this latter result, we observed improved performance in TRNI using subsets of the data compared to results using the full compendium. We identified experimental condition factors that trend with changes in TRNI performance and neff , including growth phase and media type. Finally, using the set of known E. coli genetic regulatory interactions from RegulonDB, we demonstrated that false discovery rates (FDR) derived from neff -adjusted p-values were well-matched to FDR based on the RegulonDB truth set. CONCLUSIONS: These results support utilization of neff as a potent descriptor of microarray compendia. In addition, they highlight a straightforward correlation-based method for TRNI with demonstrated meaningful statistical testing for significant edges, readily applicable to compendia from any species, even when a truth set is not available. This work facilitates a more refined approach to construction and utilization of mRNA expression compendia in TRNI.

Predicting gene targets of perturbations via network-based filtering of mRNA expression compendia.

MOTIVATION: DNA microarrays are routinely applied to study diseased or drug-treated cell populations. A critical challenge is distinguishing the genes directly affected by these perturbations from the hundreds of genes that are indirectly affected. Here, we developed a sparse simultaneous equation model (SSEM) of mRNA expression data and applied Lasso regression to estimate the model parameters, thus constructing a network model of gene interaction effects. This inferred network model was then used to filter data from a given experimental condition of interest and predict the genes directly targeted by that perturbation. RESULTS: Our proposed SSEM-Lasso method demonstrated substantial improvement in sensitivity compared with other tested methods for predicting the targets of perturbations in both simulated datasets and microarray compendia. In simulated data, for two different network types, and over a wide range of signal-to-noise ratios, our algorithm demonstrated a 167% increase in sensitivity on average for the top 100 ranked genes, compared with the next best method. Our method also performed well in identifying targets of genetic perturbations in microarray compendia, with up to a 24% improvement in sensitivity on average for the top 100 ranked genes. The overall performance of our network-filtering method shows promise for identifying the direct targets of genetic dysregulation in cancer and disease from expression profiles. AVAILABILITY: Microarray data are available at the Many Microbe Microarrays Database (M3D, http://m3d.bu.edu). Algorithm scripts are available at the Gardner Lab website (http://gardnerlab.bu.edu/SSEMLasso).

Many Microbe Microarrays Database: uniformly normalized Affymetrix compendia with structured experimental metadata.

Many Microbe Microarrays Database (M3D) is designed to facilitate the analysis and visualization of expression data in compendia compiled from multiple laboratories. M3D contains over a thousand Affymetrix microarrays for Escherichia coli, Saccharomyces cerevisiae and Shewanella oneidensis. The expression data is uniformly normalized to make the data generated by different laboratories and researchers more comparable. To facilitate computational analyses, M3D provides raw data (CEL file) and normalized data downloads of each compendium. In addition, web-based construction, visualization and download of custom datasets are provided to facilitate efficient interrogation of the compendium for more focused analyses. The experimental condition metadata in M3D is human curated with each chemical and growth attribute stored as a structured and computable set of experimental features with consistent naming conventions and units. All versions of the normalized compendia constructed for each species are maintained and accessible in perpetuity to facilitate the future interpretation and comparison of results published on M3D data. M3D is accessible at http://m3d.bu.edu/.