Development of Nine Markers and Characterization of the Microsatellite Loci in the Endangered Gymnogobius isaza (Gobiidae)

Gymnogobius isaza is a freshwater goby endemic to Lake Biwa, Japan. They experienced a drastic demographic bottleneck in the 1950s and 1980s and slightly recovered thereafter, but the population size is still very small. To reveal dynamics of genetic diversity of G. isaza, we developed nine microsatellite markers based on the sequence data of a related goby Chaenogobius annularis. Nine SSR (Simple Sequence Repeats) markers were successfully amplified for raw and formalin-fixed fish samples. The number of alleles and expected heterozygosities ranged from one to 10 and from 0.06 to 0.84, respectively, for the current samples, while one to 12 and 0.09 to 0.83 for historical samples. The markers described here will be useful for investigating the genetic diversity and gene flow and for conservation of G. isaza

Genet assignment and population structure analysis in a clonal forest-floor herb, Cardamine leucantha, using RAD-seq

To study the genetic structure of clonal plant populations, genotyping and genet detection using genetic markers are necessary to assign ramets to corresponding genets. Assignment is difficult as it involves setting a robust threshold of genetic distance for genet distinction as neighbouring genets in a plant population are often genetically related. Here, we used restriction site-associated DNA sequencing (RAD-seq) for a rhizomatous clonal herb, Cardamine leucantha [Brassicaceae] to accurately determine genet structure in a natural population. We determined a draft genome sequence of this species for the first time, which resulted in 66,617 scaffolds with N50 = 6,086 bp and an estimated genome size of approximately 253 Mbp. Using genetic distances based on the RAD-seq analysis, we successfully distinguished ramets that belonged to distinct genets even from a half-sib family. We applied these methods to 372 samples of C. leucantha collected at 1-m interval grids within a 20 × 20 m plot in a natural population in Hokkaido, Japan. From these samples, we identified 61 genets with high inequality in terms of genet size and patchy distribution. Spatial autocorrelation analyses indicated significant aggregation within 7 and 4 m at ramet and genet levels, respectively. An analysis of parallel DNA microsatellite loci (simple sequence repeats, SSR) suggested that RAD-seq can provide data that allows robust genet assignment. It remains unclear whether the large genets identified here became dominant stochastically or deterministically. Precise identification of genets will assist further study and characterization of dominant genets

Associations Between Metal Levels in Whole Blood and IgE Concentrations in Pregnant Women Based on Data From the Japan Environment and Children’s Study

Background: Metal exposures could possibly affect allergic responses in pregnant women, although no studies have yet shown a clear relationship between the two, and such exposures might also affect the development of allergic diseases in children. Methods: We investigated the relationship between metal concentrations in whole blood and immunoglobulin E (IgE; total and specific) in 14,408 pregnant women who participated in the Japan Environment and Children’s Study. The subjects submitted self-administered questionnaires, and blood samples were collected from them twice, specifically, during the first trimester and again during the second=third trimester. Concentrations of the metals Cd, Pb, Hg, Se, and Mn, as well as serum total and allergen-specific IgEs for egg white, house dust-mites (HDM), Japanese cedar pollen (JCP), animal dander, and moth, were measured. Allergen-specific IgE(s) were divided based on concentrations <0.35 or ≥0.35UA=mL, and the metal levels were divided into quartiles. Results: Multivariable logistic regression analysis showed that there was a significant negative correlation between HDM- and animal dander-specific IgEs and Hg and Mn concentrations. Conversely, there was a significant positive relationship between JCP-specific IgE and Hg and Se concentrations. Conclusions: Metal exposures may be related to both increases and decreases in allergen-specific IgEs in pregnant women.This work was supported by the Ministry of the Environment, Japan.Supplementary data related to this article can be found at https://doi.org/10.2188/jea.JE20180098

Spatial Niche Facilitates Clonal Reproduction in Seed Plants under Temporal Disturbance.

The evolutionary origins and advantages of clonal reproduction relative to sexual reproduction have been discussed for several taxonomic groups. In particular, organisms with a sessile lifestyle are often exposed to spatial and temporal environmental fluctuations. Thus, clonal propagation may be advantageous in such fluctuating environments, for sessile species that can reproduce both sexually and clonally. Here we introduce the concept of niche to a lattice space that changes spatially and temporally, by incorporating the compatibility between the characteristics of a sessile clonal plant with its habitat into a spatially explicit individual-based model. We evaluate the impact of spatially and temporally heterogeneous environments on the evolution of reproductive strategies: the optimal balance between seed and clonal reproduction of a clonal plant. The spatial niche case with local habitats led to avoidance of specialization in reproductive strategy, whereas stable environments or intensive environmental change tended to result in specialization in either clonal or seed reproduction under neutral conditions. Furthermore, an increase in spatial niches made clonal reproduction advantageous, as a consequence of competition among several genets under disturbed conditions, because a ramet reached a favorable habitat through a rare long-distance dispersal event via seed production. Thus, the existence of spatial niches could explain the advantages of clonal propagation

Floral distribution, clonal structure, and their effects on pollination success in a self-incompatible Convallaria keiskei population in northern Japan

In plant species, when clonal growth produces a patchy structure and flowering ramets are clustered, the amount of pollen contributing to reproductive success is often regulated by pollinator efficiency and geitonogamy. The spatial population structure may influence reproductive success. We examined the clonal structure, the spatial ramet distribution, and their combined effects on fruit set in a natural population of the insect-pollinated, self-incompatible clonal herb, Convallaria keiskei, in northern Japan. The number of shoots, flowers, and fruits in 1-m2 quadrats were counted at every 5 m grid point in an established 100 × 90-m study plot. From all the quadrats where shoots existed, leaf samples were collected for allozyme analysis. Using the two spatial parameters of flowering ramet densities and genotypes, we then constructed individual-based fruit-set models. A total of 236 quadrats contained shoots, and 135 contained flowering ramets, which indicated expanded distribution of this plant throughout the study plot, while shoots, flowers and fruits all showed clustering distributions. Allozyme analysis of 282 samples revealed 94 multilocus genotypes. The largest clone extended to more than 40 m, whereas 56 genotypes were detected in only one sample. Several large clones and many small clones were distributed close to each other. Fine-scale spatial modelling revealed that the neighbouring flower numbers of different genotypes, compared with local genet or flower diversity, more influenced fruit set, in which the range of the neighbour was 14.5 m. These findings indicate that the compatible pollen dispersed by insect pollinators has a significant effect on sexual reproduction, in this C. keiskei population. Consequently, the spatial structure, which includes both genet distribution and clonal expansion by ramets, had a significant effect on pollination success

The changes in reproductive strategies in response to environmental change, comparing the spatial niche and neutral cases.

<p>The spatial heterogeneity is fixed at <i>k = </i>16, and the white boxplot represent the spatial niche case and the grey boxplots represent the neutral case. Panel (a) represents the case in which frequency of environmental change is high, i.e., <i>p = </i>0.1, and panel (b) represents the case of low frequency of environmental change (<i>p = </i>0.01). Within each panel, the difference of the magnitude of environmental change is illustrated: <i>q = </i>0.1 at the top, <i>q = </i>0.01 in the middle, and <i>q</i> = 0 at the bottom. When <i>q = </i>0, it is identical to <i>p = </i>0, because it means there is no environmental change.</p

The frequency distributions of reproductive strategies in both the spatial niche and the neutral cases.

<p>The frequency of environmental change is fixed at <i>q = </i>0.1. The left side panels (a–c) represent the spatial niche case and the right side panels (d–f) represent the neutral case. The three layers of panels represent the different magnitudes of change: <i>p = </i>0.1 in the top panels (a, d), <i>p = </i>0.01 in the middle panels (b, e), and <i>p = </i>0 in the bottom panels (c, f). Within each panel, habitat heterogeneity is indicated: <i>k = </i>25 for the upper boxplot and <i>k = </i>4 for the lower boxplot. White boxplots represent the spatial niche case and the grey boxplots represent the neutral case.</p

The visual concept of spatial heterogeneity on the habitat lattice and the plant mortality rate

<p>. The figure (a) represents the concept of spatial heterogeneity. The grey scale in the squares represents the trait value (0–1) of the habitat: the value for the pure white habitat is zero and that for the pure black habitat is one. In this case, there are 16 different habitats (<i>E</i>_1,<i>t</i>, <i>E</i>_2,<i>t</i>,…<i>E</i>_16,<i>t</i>) within the total lattice space and each habitat has 2×2 square sites. The grey scale in circles represents the plant trait value (<i>Q</i>_ij). The similarity of the grey scale between <i>E</i>_l,t and <i>Q</i>_ij determines the death rate of the individual plant inhabiting (i, j), and its relationship is illustrated in (b). The two combinations of square and circle are the example of the difference between habitat and plant trait values in (b).</p

Parameters in the model.

<p>Parameters in the model.</p