Limits to adaptation along environmental gradients
Jitka Polechová, Nick Barton
Why do species not adapt to ever-wider ranges of conditions, gradually expanding their ecological niche? Theories of niche evolution typically omit spatial context, yet all species experience spatially variable conditions. Gene flow across environments has two conflicting effects on adaptation: while it increases genetic variation, which is a prerequisite for adaptation, gene flow may swamp adaptation to local conditions. We show that genetic drift can generate a sharp margin to a species’ range, by reducing genetic variance below the level needed for adaptation to spatially variable conditions. Dimensional arguments and separation of ecological and evolutionary time scales reveal a simple threshold that predicts when adaptation at the range margin fails. Two observable parameters describe the threshold: i) the effective environmental gradient, which can be measured by the loss of fitness due to dispersal to a different environment, and ii) the efficacy of selection relative to genetic drift. The theory predicts sharp range margins even in the absence of abrupt changes in the environment. Furthermore, it implies that gradual worsening of conditions across a species’ habitat may suddenly lead to range fragmentation – as adaptation to a wide span of conditions within a single species becomes impossible.
An annotated consensus genetic map for Pinus taeda L. and extent of linkage disequilibrium in three genotype-phenotype discovery populations
Jared W. Westbrook, Vikram E. Chhatre, Le-Shin Wu, Srikar Chamala, Leandro Gomide Neves, Patricio Muñoz, Pedro J Martínez-García, David B. Neale, Matias Kirst, Keithanne Mockaitis, C. Dana Nelson, Gary F. Peter, John M. Davis, Craig S. Echt
A consensus genetic map for Pinus taeda (loblolly pine) was constructed by merging three previously published maps with a map from a pseudo-backcross between P. taeda and P. elliottii (slash pine). The consensus map positioned 4981 markers via genotyping of 1251 individuals from four pedigrees. It is the densest linkage map for a conifer to date. Average marker spacing was 0.48 centiMorgans and total map length was 2372 centiMorgans. Functional predictions for 4762 markers for expressed sequence tags were improved by alignment to full-length P. taeda transcripts. Alignments to the P. taeda genome mapped 4225 scaffold sequences onto linkage groups. The consensus genetic map was used to compare the extent of genome-wide linkage disequilibrium in an association population of distantly related P. taeda individuals (ADEPT2), a multiple-family pedigree used for genomic selection studies (CCLONES), and a full-sib quantitative trait locus mapping population (BC1). Weak linkage disequilibrium was observed in CCLONES and ADEPT2. Average squared correlations, R2, between genotypes at SNPs less than one centiMorgan apart was less than 0.05 in both populations and R2 did not decay substantially with genetic distance. By contrast, strong and extended linkage disequilibrium was observed among BC1 full-sibs where average R2 decayed from 0.8 to less than 0.1 over 53 centiMorgans. The consensus map and analysis of linkage disequilibrium establish a foundation for comparative association and quantitative trait locus mapping between genotype-phenotype discovery populations.
Testing for genetic associations in arbitrarily structured populations
Minsun Song, Wei Hao, John D. Storey
We present a new statistical test of association between a trait (either quantitative or binary) and genetic markers, which we theoretically and practically prove to be robust to arbitrarily complex population structure. The statistical test involves a set of parameters that can be directly estimated from large-scale genotyping data, such as that measured in genome-wide associations studies (GWAS). We also derive a new set of methodologies, called a genotype-conditional association test (GCAT), shown to provide accurate association tests in populations with complex structures, manifested in both the genetic and environmental contributions to the trait. We demonstrate the proposed method on a large simulation study and on the Northern Finland Birth Cohort study. In the Finland study, we identify several new significant loci that other methods do not detect. Our proposed framework provides a substantially different approach to the problem from existing methods. We provide some discussion on its similarities and differences with the linear mixed model and principal component approaches.
The competition between simple and complex evolutionary trajectories in asexual populations
Ian E. Ochs, Michael M. Desai
Comments: 8 pages, 3 figures
Subjects: Populations and Evolution (q-bio.PE)
On rugged fitness landscapes where sign epistasis is common, adaptation can often involve either individually beneficial “uphill” mutations or more complex mutational trajectories involving fitness valleys or plateaus. The dynamics of the evolutionary process determine the probability that evolution will take any specific path among a variety of competing possible trajectories. Understanding this evolutionary choice is essential if we are to understand the outcomes and predictability of adaptation on rugged landscapes. We present a simple model to analyze the probability that evolution will eschew immediately uphill paths in favor of crossing fitness valleys or plateaus that lead to higher fitness but less accessible genotypes. We calculate how this probability depends on the population size, mutation rates, and relevant selection pressures, and compare our analytical results to Wright-Fisher simulations. We find that the probability of valley crossing depends nonmonotonically on population size: intermediate size populations are most likely to follow a “greedy” strategy of acquiring immediately beneficial mutations even if they lead to evolutionary dead ends, while larger and smaller populations are more likely to cross fitness valleys to reach distant advantageous genotypes. We explicitly identify the boundaries between these different regimes in terms of the relevant evolutionary parameters. Above a certain threshold population size, we show that the degree of evolutionary “foresight” depends only on a single simple combination of the relevant parameters.
The genomic signature of social interactions regulating honey bee caste development
Svjetlana Vojvodic, Brian R Johnson, Brock Harpur, Clement Kent, Amro Zayed, Kirk E Anderson, Timothy Linksvayer
Social evolution theory posits the existence of genes expressed in one individual that affect the traits and fitness of social partners. The archetypal example of reproductive altruism, honey bee reproductive caste, involves strict social regulation of larval caste fate by care-giving nurses. However, the contribution of nurse-expressed genes, which are prime socially-acting candidate genes, to the caste developmental program and to caste evolution remains mostly unknown. We experimentally induced new queen production by removing the current colony queen, and we used RNA sequencing to study the gene expression profiles of both developing larvae and their care-giving nurses before and after queen removal. By comparing the gene expression profiles between both queen-destined larvae and their nurses to worker-destined larvae and their nurses in queen-present and queen-absent conditions, we identified larval and nurse genes associated with larval caste development and with queen presence. Of 950 differentially-expressed genes associated with larval caste development, 82% were expressed in larvae and 18% were expressed in nurses. Behavioral and physiological evidence suggests that nurses may specialize in the short term feeding queen- versus worker-destined larvae. Estimated selection coefficients indicated that both nurse and larval genes associated with caste are rapidly evolving, especially those genes associated with worker development. Of the 1863 differentially-expressed genes associated with queen presence, 90% were expressed in nurses. Altogether, our results suggest that socially-acting genes play important roles in both the expression and evolution of socially-influenced traits like caste.
Evaluating intra- and inter-individual variation in the human placental transcriptome
David A Hughes, Martin Kircher, Zhisong He, Song Guo, Genevieve L Fairbrother, Carlos S Moreno, Philipp Khaitovich, Mark Stoneking
Background: Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta. Results: We estimate that on average, 33.2%, 58.9% and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling and metabolism. Many biological traits demonstrated correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome (65% of expressed genes) exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection (26%), directional selection (4.9%), or diversifying selection (4.8%). Conclusion: We apportion placental gene expression variation into individual, population and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection.
The rate and molecular spectrum of spontaneous mutations in the GC-rich multi-chromosome genome of Burkholderia cenocepacia
Marcus M Dillon, Way Sung, Michael Lynch, Vaughn S Cooper
Spontaneous mutations are ultimately essential for evolutionary change and are also the root cause of nearly all disease. However, until recently, both biological and technical barriers have prevented detailed analyses of mutation profiles, constraining our understanding of the mutation process to a few model organisms and leaving major gaps in our understanding of the role of genome content and structure on mutation. Here, we present a genome-wide view of the molecular mutation spectrum in Burkholderia cenocepacia, a clinically relevant pathogen with high %GC content and multiple chromosomes. We find that B. cenocepacia has low genome-wide mutation rates with insertion-deletion mutations biased towards deletions, consistent with the idea that deletion pressure reduces prokaryotic genome sizes. Unlike previously assayed organisms, B. cenocepacia exhibits a GC-mutation bias, which suggests that at least some genomes with high GC content may be driven to this point by unusual base-substitution mutation pressure. Notably, we also observed variation in both the rates and spectra of mutations among chromosomes, and a significant elevation of G:C>T:A transversions in late-replicating regions. Thus, although some patterns of mutation appear to be highly conserved across cellular life, others vary between species and even between chromosomes of the same species, potentially influencing the evolution of nucleotide composition and genome architecture.