Potential Distribution of Six North American Higher-Attine Fungus-Farming Ant (Hymenoptera: Formicidae) Species

Ants are among the most successful insects in Earth’s evolutionary history. However, there is a lack of knowledge regarding range-limiting factors that may influence their distribution. The goal of this study was to describe the environmental factors (climate and soil types) that likely impact the ranges of five out of the eight most abundant Trachymyrmex species and the most abundant Mycetomoellerius species in the United States. Important environmental factors may allow us to better understand each species’ evolutionary history. We generated habitat suitability maps using MaxEnt for each species and identified associated most important environmental variables. We quantified niche overlap between species and evaluated possible congruence in species distribution. In all but one model, climate variables were more important than soil variables. The distribution of M. turrifex (Wheeler, W.M., 1903) was predicted by temperature, specifically annual mean temperature (BIO1), T. arizonensis (Wheeler, W.M., 1907), T. carinatus, and T. smithi Buren, 1944 were predicted by precipitation seasonality (BIO15), T. septentrionalis (McCook, 1881) were predicted by precipitation of coldest quarter (BIO19), and T. desertorum (Wheeler, W.M., 1911) was predicted by annual flood frequency. Out of 15 possible pair-wise comparisons between each species’ distributions, only one was statistically indistinguishable (T. desertorum vs T. septentrionalis). All other species distribution comparisons show significant differences between species. These models support the hypothesis that climate is a limiting factor in each species distribution and that these species have adapted to temperatures and water availability differently

Variation in Arabidopsis Flowering Time Associated with Cis-Regulatory Variation in CONSTANS

The onset of flowering, the change from vegetative to reproductive development, is a major life history transition in flowering plants. Recent work suggests that mutations in cis-regulatory mutations should play critical roles in the evolution of this (as well as other) important adaptive traits, but thus far there has been little evidence that directly links regulatory mutations to evolutionary change at the species level. While several genes have previously been shown to affect natural variation in flowering time in Arabidopsis thaliana, most either show protein-coding changes and/or are found at low frequency (\u3c5%). Here we identify and characterize natural variation in the cis-regulatory sequence in the transcription factor CONSTANS that underlies flowering time diversity in Arabidopsis. Mutation in this regulatory motif evolved recently and has spread to high frequency in Arabidopsis natural accessions, suggesting a role for these cis-regulatory changes in adaptive variation of flowering time

Spin-Isospin Modes in Heavy-Ion Collisions

Plant development is remarkably plastic but how precisely can the plant customize its form to specific environments When the plant adjusts its development to different environments, related traits can change in a coordinated fashion, such that two traits co-vary across many genotypes. Alternatively, traits can vary independently, such that a change in one trait has little predictive value for the change in a second trait. To characterize such ‘‘tunability’’ in developmental plasticity, we carried out a detailed phenotypic characterization of complex root traits among 96 accessions of the model Arabidopsis thaliana in two nitrogen environments. The results revealed a surprising level of independence in the control of traits to environment – a highly tunable form of plasticity. We mapped genetic architecture of plasticity using genome-wide association studies and further used gene expression analysis to narrow down gene candidates in mapped regions. Mutants in genes implicated by association and expression analysis showed precise defects in the predicted traits in the predicted environment, corroborating the independent control of plasticity traits. The overall results suggest that there is a pool of genetic variability in plants that controls traits in specific environments, with opportunity to tune crop plants to a given environment

Changes in root traits among natural variants in two different nitrogen environments.

<p>The difference between root trait values on low and high nitrogen (δ highN-lowN) is represented in the form of individual bar charts (A) and trait differences were used to form a dendrogram of accessions resulting in nine clusters as indicated by horizontal lines (B); the seven accessions chosen for expression analysis are highlighted in red. (C) Images of low N and high N grown seedlings from representative accessions of a ‘strong N-responder’ Sq-8, a ‘weak N-responder’ NFA-8, and the ‘super N-responder’ Kas-2 with yellow highlighting on their trait difference values on (A); scale bars = 1 cm. (D–E) PCA analysis of the δ highN-lowN for the seven accessions. Red markers indicate position of 96 accessions as determined by their trait values in the given principal components. Blue lines represent vectors that quantify the magnitude and direction of a trait's contribution to that axis. For example, in (E), an accession with a high score in PC3 will have a high LRtot value. PC2 is not informative for LRtot but accessions with a long primary root (PR) will score highly on this axis. The percent variability explained by PCs 1, 2 and 3 are 64%, 17%, and 10%, respectively.</p

Functional validation of root architecture regulators <i>JR1</i> (A–C), <i>PhzC/PhF</i> (D–F), and <i>UBQ14</i> (G–I).

<p>(A,D,G) Genome-wide <i>P</i> values from the GWAS magnified around SNP hits; horizontal dashed line corresponds to the 5% FDR threshold that corrects for multiple simultaneous tests. Genes within the 20 Kb boundary around the SNP hits are represented with bars; red color denotes genes whose expression changes in response to nitrogen or among accessions (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003760#pgen.1003760.s021" target="_blank">Table S11</a>), asterisks denote mutants with phenotypes, arrow denotes the gene described in each panel. (B,E,H) Images of four 12 day old seedlings grown on low or high N for two T-DNA alleles in each gene and Col-0; scale bars = 1 cm. (C,F,I) GWAS prediction on trait phenotypes (yellow) and observed phenotypes from confirmed T-DNA alleles indicated with arrows with <i>P</i> value, where arrow denotes direction of change in mutant vs. wild type and <i>t</i>-test <i>P</i> value shows significance of the trait difference in mutant vs. wild type (denoted with first three SALK digits); see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003760#pgen.1003760.s022" target="_blank">Table S12</a>.</p

Global expression analysis of genes differentially regulated by nitrogen across representative accessions.

<p>(A) A heatmap showing cluster patterns of N responses across accessions ordered by clustering on Euclidean distance; see color scale bar for log2 fold change magnitude and direction. Among N*Accession genes, the GO terms ‘response to stimulus’ (30 genes, <i>P</i> = 8.5E-03), and ‘RNA binding’ (9 genes, <i>P</i> = 8.1E-03) were both overrepresentated; BioMaps GO term overrepresentation analysis. (B,D,F) Average log2 microarray expression values for three representative gene response clusters in control and N-treated experiments. (C,E,G) Row mean (per gene)-normalized expression levels of individual genes are plotted for all genes within the three clusters shown in B,D,F (colored lines), together with the centroid for each cluster (black line); lines are used to connect expression levels between accession control and N-treated experiments for visualization purposes. (B,C) A N-induced cluster in all accessions (N,Accession cluster 14, <i>n</i> = 28) in which ‘response to nitrate’ is overrepresented (2 genes, <i>P</i> = 2.7E-03). (D,E) A N-repressed cluster in all accessions (N,Accession cluster 5, <i>n</i> = 8), in which ‘nucleic acid binding transcription factor activity’ is overrepresented (3 genes, <i>P</i> = 8.4E-03). (F,G) A N-regulated cluster with differential induction in accessions (N*Accession cluster 1, <i>n</i> = 14), in which ‘cyclin-dependent protein kinase (CDK) inhibitor activity’ is overrepresented (1 gene, <i>P</i> = 5.2E-03).</p

Clustering of 96 accessions grown on high nitrogen and low nitrogen based on root traits.

<p>(A) Clustering based on low N traits (scaled) forms eight clusters, which are indicated by vertical lines next to the dendrogram. Accessions within correlated groups (clusters) are highlighted in different colors. (B) Clustering based on high N traits (scaled) forms six clusters. The cluster designations in low N are highlighted in the same color as used in (A), illustrating the alternate topologies in different environments. (A–B) Adjacent to each dendrogram is a heatmap visualizing the scaled trait values for each ecotype; see color scale bar for values. Several examples of average seedling root architecture are shown for the seven accessions chosen for expression analysis (red text) and five additional accessions to illustrate root architecture in each cluster. Scale bars = 1 cm.</p