PCoA plot based on RAPDs variation, with the first two principal components showing relationships among the 11 populations of <i>Fritillaria tubiformis</i> studied.

<p>PCoA plot based on RAPDs variation, with the first two principal components showing relationships among the 11 populations of <i>Fritillaria tubiformis</i> studied.</p

Geographical distribution of the Italian populations of <i>Fritillaria tubiformis</i> subsp. <i>moggridgei</i> (circles) and <i>Fritillaria tubiformis</i> var. <i>burnatii</i> (stars) analysed in this study.

<p>Geographical distribution of the Italian populations of <i>Fritillaria tubiformis</i> subsp. <i>moggridgei</i> (circles) and <i>Fritillaria tubiformis</i> var. <i>burnatii</i> (stars) analysed in this study.</p

Probability of assignment of 264 plants of <i>Fritillaria tubiformis</i> from Italy to the two genetic clusters identified by hierarchical STRUCTURE analysis, and corresponding with subspecific taxa.

<p>Each vertical bar corresponds with a distinct genotype and different colours indicate the part of its genome assigned to each cluster. M =  <i>Fritillaria tubiformis</i> subsp. <i>moggridgei</i>, B =  <i>Fritillaria tubiformis</i> var. <i>burnatii</i>.</p

Dendrogram based on UPGMA of RAPDs profiles, showing relationships among the 11 populations of <i>Fritillaria tubiformis</i> considered in the study.

<p>M =  <i>Fritillaria tubiformis</i> subsp. <i>moggridgei</i>, B =  <i>Fritillaria tubiformis</i> var. <i>burnatii</i>.</p

Genetic variation within populations of <i>Fritillaria tubiformis</i> from Italy, based on 201 RAPD markers.

<p>*M =  Fritillaria tubiformis subsp. moggridgei, B =  Fritillaria tubiformis var. burnatii.</p><p>S =  sample size, N =  mean number of alleles per locus, N_e  =  effective number of alleles per locus, P =  percentage of polymorphic loci (95% criterion), H_e  =  Nei's (1978) unbiased expected gene diversity, I =  Shannon's index over loci. Standard errors are given in parenthesis.</p

Characteristics of fragments generated by the 8 primers selected for the genetic analysis.

<p>Characteristics of fragments generated by the 8 primers selected for the genetic analysis.</p

<i>In Vitro</i> Morphogenesis of <i>Arabidopsis</i> to Search for Novel Endophytic Fungi Modulating Plant Growth

<div><p>Fungal endophytes have shown to affect plant growth and to confer stress tolerance to the host; however, effects of endophytes isolated from water plants have been poorly investigated. In this study, fungi isolated from stems (stem-E) and roots (root-E) of <i>Mentha aquatica</i> L. (water mint) were identified, and their morphogenetic properties analysed on <i>in vitro</i> cultured <i>Arabidopsis</i> (L.) Heynh., 14 and 21 days after inoculation (DAI). Nineteen fungi were analysed and, based on ITS analysis, 17 isolates showed to be genetically distinct. The overall effect of water mint endophytes on <i>Arabidopsis</i> fresh (FW) and dry weight (DW) was neutral and positive, respectively, and the increased DW, mainly occurring 14 DAI, was possibly related to plant defence mechanism. Only three fungi increased both FW and DW of <i>Arabidopsis</i> at 14 and 21 DAI, thus behaving as plant growth promoting (PGP) fungi. E-treatment caused a reduction of root depth and primary root length in most cases and inhibition-to-promotion of root area and lateral root length, from 14 DAI. Only <i>Phoma macrostoma</i>, among the water mint PGP fungi, increased both root area and depth, 21 DAI. Root depth and area 14 DAI were shown to influence DWs, indicating that the extension of the root system, and thus nutrient uptake, was an important determinant of plant dry biomass. Reduction of <i>Arabidopsis</i> root depth occurred to a great extent when plants where treated with stem-E while root area decreased or increased under the effects of stem-E and root-E, respectively, pointing to an influence of the endophyte origin on root extension. <i>M</i>. <i>aquatica</i> and many other perennial hydrophytes have growing worldwide application in water pollution remediation. The present study provided a model for directed screening of endophytes able to modulate plant growth in the perspective of future field applications of these fungi.</p></div

Endophyte effects on fresh weights.

<p>(a, b) Boxplots illustrating variability of fresh weight in E-treated and control (C) <i>Arabidopsis</i> plants 14 (a) and 21 (b) DAI. The reference hatched line represents the median of controls. Differences were considered significant at a probability level of *: p<0.05; **: <0.01; and ***: <0.001. (c, d) Pooled data for controls (C) and plants treated with all (E), stem (stem-E) and root (root-E) endophytes and 14 (a) and 21 (b) DAI.</p

Endophyte effects on dry weights.

<p>(a, b) Boxplots illustrating variability of dry weight in E-treated and control (C) <i>Arabidopsis</i> plants 14 (a) and 21 (b) DAI. The reference hatched line represents the median of controls. Differences were considered significant at a probability level of *: p<0.05; **: <0.01; and ***: <0.001. (c, d) Pooled data for controls (C) and plants treated with all (E), stem (stem-E) and root (root-E) endophytes and 14 (a) and 21 (b) DAI.</p

Endophyte effects on percentage dry weights.

<p>(a, b) Boxplots illustrating variability of percentage dry weight in E-treated and control (C) <i>Arabidopsis</i> plants 14 (a) and 21 (b) DAI. The reference hatched line represents the median of controls. Differences were considered significant at a probability level of *: P<0.05; **: <0.01; and ***: <0.001. (c, d) Pooled data for controls (C) and plants treated with all (E), stem (stem-E) and root (root-E) endophytes and 14 (a) and 21 (b) DAI.</p