Monodispersed Renewable Particles by Cascade and Density Gradient Size Fractionation to Advance Lignin Nanotechnologies

Control over particle size and shape heterogeneity is highly relevant to the design of photonic coatings and supracolloidal assemblies. Most developments in the area have relied on mineral and petroleum-derived polymers that achieve well-defined chemical and dimensional characteristics. Unfortunately, it is challenging to attain such control when considering renewable nanoparticles. Herein, a pathway toward selectable biobased particle size and physicochemical profiles is proposed. Specifically, lignin is fractionated, a widely available heterogeneous polymer that can be dissolved in aqueous solution, to obtain a variety of monodispersed particle fractions. A two-stage cascade and density gradient centrifugation that relieves the need for solvent pre-extraction or other pretreatments but achieves particle bins of uniform size (~60 to 860 nm and polydispersity, PDI<0.06, dynamic light scattering) along with characteristic surface chemical features is introduced. It is found that the properties and associated colloidal behavior of the particles are suitably classified in distinctive size populations, namely, i) nanoscale (50-100 nm), ii) photonic (100-300 nm) and iii) near-micron (300-1000 nm). The strong correlation that exists between size and physicochemical characteristics (molar mass, surface charge, bonding and functional groups, among others) is introduced as a powerful pathway to identify nanotechnological uses that benefit from the functionality and cost-effectiveness of biogenic particles.

How useful are genomic data for predicting maladaptation to future climate?

Methods using genomic information to forecast potential population maladaptation to climate change or new environments are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods-Gradient Forests (GFoffset) and the risk of non-adaptedness (RONA)-using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against 2- and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GFoffset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use.

Weak local adaptation to drought in seedlings of a widespread conifer

Tree seedlings from populations native to drier regions are often assumed to be more drought tolerant than those from wetter provenances. However, intraspecific variation in drought tolerance has not been well-characterized despite being critical for developing climate change mitigation and adaptation strategies, and for predicting the effects of drought on forests. We used a large-scale common garden drought-to-death experiment to assess range-wide variation in drought tolerance, measured by decline of photosynthetic efficiency, growth, and plastic responses to extreme summer drought in seedlings of 73 natural populations of the two main varieties of Douglas-fir (Pseudotsuga menziesii var. menziesii and var. glauca). Local adaptation to drought was weak in var. glauca and nearly absent in menziesii. Var. glauca showed higher tolerance to drought but slower growth than var. menziesii. Clinal variation in drought tolerance and growth species-wide was mainly associated with temperature rather than precipitation. A higher degree of plasticity for growth was observed in var. menziesii in response to extreme drought. Genetic variation for drought tolerance in seedlings within varieties is maintained primarily within populations. Selective breeding within populations may facilitate adaptation to drought more than assisted gene flow.

Modularity of genes involved in local adaptation to climate despite physical linkage

BACKGROUND

Linkage among genes experiencing different selection pressures can make natural selection less efficient. Theory predicts that when local adaptation is driven by complex and non-covarying stresses, increased linkage is favored for alleles with similar pleiotropic effects, with increased recombination favored among alleles with contrasting pleiotropic effects. Here, we introduce a framework to test these predictions with a co-association network analysis, which clusters loci based on differing associations. We use this framework to study the genetic architecture of local adaptation to climate in lodgepole pine, Pinus contorta, based on associations with environments.

RESULTS

We identify many clusters of candidate genes and SNPs associated with distinct environments, including aspects of aridity and freezing, and discover low recombination rates among some candidate genes in different clusters. Only a few genes contain SNPs with effects on more than one distinct aspect of climate. There is limited correspondence between co-association networks and gene regulatory networks. We further show how associations with environmental principal components can lead to misinterpretation. Finally, simulations illustrate both benefits and caveats of co-association networks.

CONCLUSIONS

Our results support the prediction that different selection pressures favor the evolution of distinct groups of genes, each associating with a different aspect of climate. But our results went against the prediction that loci experiencing different sources of selection would have high recombination among them. These results give new insight into evolutionary debates about the extent of modularity, pleiotropy, and linkage in the evolution of genetic architectures.