DNA barcoding of <i>Actinidia</i> (Actinidiaceae) using internal transcribed spacer, <i>matK</i>, <i>rbcL</i> and <i>trnH</i>-<i>psbA</i>, and its taxonomic implication

<p><i>Actinidia</i> is taxonomically difficult and economically important. Four traditional barcoding markers, internal transcribed spacer (ITS), <i>rbcL</i>, <i>matK</i> and <i>trnH</i>-<i>psbA</i>, were used to identify the 29 <i>Actinidia</i> species sampled. High-quality sequences could be obtained easily for <i>rbcL</i>, <i>matK</i> and <i>trnH</i>-<i>psbA</i>, and <i>matK</i> performed best at resolving species among these three markers. ITS had a moderate sequencing success of 72% and the species resolution proportion was 60.7%. Sequencing success rate for <i>matK </i>+ <i>rbcL</i> was 97.4% and it discriminated 48.3% of the species analysed. The barcode <i>trnH</i>-<i>psbA</i> could only identify <i>Actinidia eriantha. MatK </i>+ <i>rbcL</i> and ITS are useful markers to barcode <i>Actinidia</i>; the utility of ITS in barcoding needs further investigation using high-throughput sequencing technology. Phylogenetic analyses based on ITS, <i>matK</i>, <i>matK </i>+ <i>rbcL</i> and <i>matK </i>+ <i>rbcL </i>+ <i>trnH</i>-<i>psbA</i> indicated Sect. <i>Leiocarpae</i> to be paraphyletic, while Sect. <i>Maculatae</i> and Sect. <i>Strigosae</i> together with Sect. <i>Stellatae</i> formed a monophyletic group. We recommended the subdivision of <i>Actinidia</i> into two groups: one consisting of Sect. <i>Leiocarpae</i> (ovaries glabrous, fruits spotless), and the other comprising sections <i>Maculatae</i>, <i>Strigosae</i> and <i>Stellatae</i> (ovaries hairy, fruits spotted). This study supported the separation of <i>Actinidia chinensis</i> var. <i>chinensis</i> and var. <i>deliciosa</i> at the infraspecific level, and the separation of <i>Actinidia tetramera</i> and <i>Actinidia kolomikta</i> at the specific level. The treatment of <i>Actinidia maloides</i> as a synonym of <i>A</i>. <i>kolomikta</i> and <i>Actinidia cinerascen</i>s as a variety of <i>Actinidia fulvicoma</i> was also warranted.</p

Simultaneous 3D Construction and Imaging of Plant Cells Using Plasmonic Nanoprobe Assisted Multimodal Nonlinear Optical Microscopy

Nonlinear optical (NLO) imaging has emerged as a promising plant cell imaging technique due to its large optical penetration, inherent 3D spatial resolution, and reduced photodamage, meanwhile exogenous nanoprobes are usually needed for non-signal target cell analysis. Here, we report in-vivo, simultaneous 3D labeling and imaging of potato cell structures using plasmonic nanoprobe-assisted multimodal NLO microscopy. Experimental results show that the complete cell structure could be imaged by the combination of second-harmonic generation (SHG) and two-photon luminescence (TPL) when noble metal silver or gold ions are added. In contrast, without noble metal ion solution, no NLO signals from the cell wall could be acquired. The mechanism can be attributed to noble metal nanoprobes with strong nonlinear optical responses formed along the cell walls via a femtosecond laser scan. During the SHG-TPL imaging process, noble metal ions that cross the cell wall could be rapidly reduced to plasmonic nanoparticles by fs laser and selectively anchored onto both sides of the cell wall, thereby leading to simultaneous 3D labeling and imaging of potato cells. Compared with traditional labeling technique that needs in-vitro nanoprobe fabrication and cell labeling, our approach allows for one-step, in-vivo labeling of plant cells, thus providing a rapid, cost-effective way for cellular structure construction and imaging

PIG879822 Supplemental Material - Supplemental material for Design of iron bird for a regional jet aircraft

Supplemental material, PIG879822 Supplemental Material for Design of iron bird for a regional jet aircraft by Li Dawei, Lin Mingxing and Tian Liang in Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering</p

Influence of Oxygen Ligation on [Fe₄S₄] Cluster Properties. Characterization of the Cys77Ser Mutant of <i>Chromatium vinosum </i>HiPIP

Influence of Oxygen Ligation on [Fe4S4] Cluster Properties. Characterization of the Cys77Ser Mutant of Chromatium vinosum HiPI

Influence of Oxygen Ligation on [Fe₄S₄] Cluster Properties. Characterization of the Cys77Ser Mutant of <i>Chromatium vinosum </i>HiPIP

Influence of Oxygen Ligation on [Fe4S4] Cluster Properties. Characterization of the Cys77Ser Mutant of Chromatium vinosum HiPI

Multilocus genetic and epigenetic differentiations between <i>Actinidia chinensis</i> cytotypes using analyses of molecular variance (AMOVA).

<p>*<i>P</i> values based on 10 0000 permutations</p><p>Multilocus genetic and epigenetic differentiations between <i>Actinidia chinensis</i> cytotypes using analyses of molecular variance (AMOVA).</p

Principal components analysis (PCA) for morphological (a) and molecular variation (c: genetic; d: epigenetic), and (b) canonical correspondence analysis (CCA) for environmental variables and cytotype distribution of <i>Actinidia chinensis</i>.

<p>PCAs (a, c and d) only present the first two principal components and ellipses represent the dispersion of those points around their center. Abbreviations in PCA analysis of morphological variation are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117596#pone.0117596.s002" target="_blank">S2 Table</a> and abbreviations in CCA analysis are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117596#pone.0117596.t001" target="_blank">Table 1</a>.</p

The Microgeographical Patterns of Morphological and Molecular Variation of a Mixed Ploidy Population in the Species Complex <i>Actinidia chinensis</i>

<div><p>Polyploidy and hybridization are thought to have significant impacts on both the evolution and diversification of the genus <i>Actinidia</i>, but the structure and patterns of morphology and molecular diversity relating to ploidy variation of wild <i>Actinidia</i> plants remain much less understood. Here, we examine the distribution of morphological variation and ploidy levels along geographic and environmental variables of a large mixed-ploidy population of the <i>A. chinensis</i> species complex. We then characterize the extent of both genetic and epigenetic diversity and differentiation exhibited between individuals of different ploidy levels. Our results showed that while there are three ploidy levels in this population, hexaploids were constituted the majority (70.3%). Individuals with different ploidy levels were microgeographically structured in relation to elevation and extent of niche disturbance. The morphological characters examined revealed clear difference between diploids and hexaploids, however tetraploids exhibited intermediate forms. Both genetic and epigenetic diversity were high but the differentiation among cytotypes was weak, suggesting extensive gene flow and/or shared ancestral variation occurred in this population even across ploidy levels. Epigenetic variation was clearly correlated with changes in altitudes, a trend of continuous genetic variation and gradual increase of epigenomic heterogeneities of individuals was also observed. Our results show that complex interactions between the locally microgeographical environment, ploidy and gene flow impact <i>A. chinensis</i> genetic and epigenetic variation. We posit that an increase in ploidy does not broaden the species habitat range, but rather permits <i>A. chinensis</i> adaptation to specific niches.</p></div

Supplementary tables from Peli1 Modulates the Subcellular Localization and Activity of Mdmx

Proteins identified in the MDMX complex and Demographic and clinical characteristics in the patients with cutaneous melanoma</p

Population genetic and epigenetic structure subdivisions detected in STRUCTURE.

<p>(a) <i>Actinidia chinensis</i> individuals grouped by ploidy levels and (b) sorted out by sampling sites along altitudinal changes (Low → High). The four different colors in the first row represent four main genetic clusters (<i>K</i> = 4, red: cluster I; green: cluster II; yellow: cluster III; blue: cluster IV) and three colors in the second row represent three epigenetic clusters (<i>K</i> = 3, red: cluster I; green: cluster II; yellow: cluster III).</p