Convergence, Consilience, and the Evolution of Temperate Deciduous Forests.

The deciduous habit of northern temperate trees and shrubs provides one of the most obvious examples of convergent evolution, but how did it evolve? Hypotheses based on the fossil record posit that deciduousness evolved first in response to drought or darkness and preadapted certain lineages as cold climates spread. An alternative is that evergreens first established in freezing environments and later evolved the deciduous habit. We monitored phenological patterns of 20 species of Viburnum spanning tropical, lucidophyllous (subtropical montane and warm temperate), and cool temperate Asian forests. In lucidophyllous forests, all viburnums were evergreen plants that exhibited coordinated leaf flushes with the onset of the rainy season but varied greatly in the timing of leaf senescence. In contrast, deciduous species exhibited tight coordination of both flushing and senescence, and we found a perfect correlation between the deciduous habit and prolonged annual freezing. In contrast to previous stepwise hypotheses, a consilience of independent lines of evidence supports a lockstep model in which deciduousness evolved in situ, in parallel, and concurrent with a gradual cooling climate. A pervasive selective force combined with the elevated evolutionary accessibility of a particular response may explain the massive convergence of adaptive strategies that characterizes the world's biomes.

Development of HGF-binding aptamers with the combination of G4 promoter-derived aptamer selection and in silico maturation.

We describe the selection of aptamers based on bioinformatics-based approaches without Systematic Evolution of Ligands by EXponential enrichment (SELEX). SELEX is a potent method; however, it is time intensive and the PCR-amplification step, which is essential step for SELEX, leads to the loss of good aptamers. We have developed an aptamer-screening method, G4 promoter-derived aptamer selection (G4PAS), and an aptamer-improving method, in silico maturation (ISM). They are based on in silico sequence selection and computer assisted directed evolution, respectively. In this study, we succeeded in identifying new aptamers against hepatocyte growth factor (HGF) by G4PAS as well as improving the specificity of the HGF aptamers by ISM. Using ISM improved the specificity of the aptamer for HGF by up to 45-fold in comparison with the original aptamer. These methods enable easy and efficient identification of good aptamers, and the combination of G4PAS with ISM can thus serve as a potent approach for aptamer identification. Biotechnol. Bioeng. 2017;114: 2196-2203. © 2017 Wiley Periodicals, Inc.

Data on G-quadruplex topology, and binding ability of G-quadruplex forming sequences found in the promoter region of biomarker proteins and those relations to the presence of nuclear localization signal in the proteins.

Aptamer is a nucleic acid ligand which specifically binds to its target molecule. Previously, we have designed an identification method of aptamer called "G-quadruplex (G4) promoter-derived aptamer selection (G4PAS)" [1]. In G4PAS procedure, putative G4 forming sequences (PQS) were explored in a promoter region of a target protein in human gene through computational analysis, and evaluated binding ability towards the gene product encoded in the downstream of the promoter. We investigated the topology of the obtained PQSs by circular dichroism measurement, as well as their binding ability against its target protein by surface plasmon resonance measurement and gel-shift assay. Additionally, the presence of nuclear localization signal in the target protein was predicted in silico. This data set summarized all the PQS sequences, their biochemical characteristics, and the presence of nuclear localization signal to address the possibility of binding of these PQS region to the target proteins in vivo. Those data should contribute to increase the success rate of G4PAS. Moreover, considering the G4 motifs in genomic DNA are suggested to be involved in vivo gene regulation [2], [3], this data set is also potentially beneficial for the cell biology field.