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Ecological speciation has long been noted as a central topic in the field of evolutionary biology, and investigation into the relative importance of ecological and geographical factors is becoming increasingly emphasized. We surveyed genetic variation of 277 samples from 25 populations of nine Rhododendron species within Tsutsusi subgenus in Taiwan using simple sequence repeats of expressed sequence tags. Bayesian clustering revealed four genetic lineages: (1) the Rhododendron simsii, Rhododendron kanehirai, and Rhododendron nakaharae lineage (lineage 1); (2) the R h o d o d e n d ro n l o n g i p e r u l a t u m , R h o d o d e n d ro n breviperulatum, and Rhododendron noriakianum lineage (lineage 2); (3) the Rhododendron rubropilosum lineage (lineage 3); and (4) the Rhododendron oldhamii lineage (lineage 4).Asymmetric introgressions were found from lineage 3 into lineages 1 and 2 (introgressed lineages). Genetic admixture of non-R. oldhamii species was also revealed by a neighborjoining tree. Variation partitioning showed that environment explained much larger portions of genetic variation than geography between non-introgressed lineages (i.e., between R. oldhamii and other lineages). However, the Mantel and partial Mantel tests and the multiple matrix regression with randomization found that isolation-by-distance played a more important role than isolation-by-environment (IBE) in contributing to genetic variation in most between lineage comparisons. Nevertheless, strong IBE was found when compared between non-introgressed lineages of R. oldhamii and R. rubropilosum, suggesting post-speciation ecological divergence. Several environmental variables, including annual mean temperature, aspect, isothermality, seasonal precipitation, slope, and soil pH, could be important ecological drivers involved in reproductive isolation between R. oldhamii and non-R. oldhamii species within the Tsutsusi subgenus.

Chemical shifts of amino acids in proteins are the most sensitive and easily obtainable NMR parameters that reflect the primary, secondary, and tertiary structures of the protein. In recent years, chemical shifts have been used to identify secondary structure in peptides and proteins, and it has been confirmed that (1)H(alpha), (13)C(alpha), (13)C(beta), and (13)C' NMR chemical shifts for all 20 amino acids are sensitive to their secondary structure. Currently, most of the methods are purely based on one-dimensional statistical analyses of various chemical shifts for each residue to identify protein secondary structure. However, it is possible to achieve an increased accuracy from the two-dimensional analyses of these chemical shifts. The 2DCSi approach performs two-dimension cluster analyses of (1)H(alpha), (1)H(N), (13)C(alpha), (13)C(beta), (13)C', and (15)N(H) chemical shifts to identify protein secondary structure and the redox state of cysteine residue. For the analysis of paired chemical shifts of 6 data sets, each of the 20 amino acids has its own 15 two-dimension cluster scattering diagrams. Accordingly, the probabilities for identifying helix and extended structure were calculated by using our scoring matrix. Compared with existing the chemical shift-based methods, it appears to improve the prediction accuracy of secondary structure identification, particularly in the extended structure. In addition, the probability of the given residue to be helix or extended structure is displayed, allows the users to make decisions by themselves.

Genetic variation evolves during postglacial range expansion of a species and is important for adapting to varied environmental conditions. It is crucial for the future survival of a species. We investigate the nuclear DNA sequence variation to provide evidence of postglacial range expansion of Musa basjoo var. formosana, a wild banana species, and test for adaptive evolution of amplified fragment length polymorphic (AFLP) loci underlying local adaptation in association with environmental variables. Postglacial range expansion was suggested by phylogeographical analyses based on sequence variation of the second intron of copper zinc superoxide dismutase 2 gene. Two glacial refugia were inferred by the average F ST parameter (mean F ST of a population against the remaining populations). Using variation partitioning by redundancy analysis, we found a significant amount of explained AFLP variation attributed to environmental and spatially-structured environmental effects. By combining genome scan methods and multiple univariate logistic regression, four AFLP loci were found to be strongly associated with environmental variables, including temperature, precipitation, soil moisture, wet days, and surface coverage activity representing vegetation greenness. These environmental variables may have played various roles as ecological drivers for adaptive evolution of M. basjoo var. formosana during range expansion after the last glacial maximum.