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Co-evolution in a landrace meta-population: two closely related pathogens interacting with the same host can lead to different adaptive outcomes

Identifieur interne : 000085 ( Pmc/Curation ); précédent : 000084; suivant : 000086

Co-evolution in a landrace meta-population: two closely related pathogens interacting with the same host can lead to different adaptive outcomes

Auteurs : Domenico Rau [Italie] ; Monica Rodriguez [Italie] ; Maria Leonarda Murgia [Italie] ; Virgilio Balmas [Italie] ; Elena Bitocchi [Italie] ; Elisa Bellucci [Italie] ; Laura Nanni [Italie] ; Giovanna Attene [Italie] ; Roberto Papa [Italie]

Source :

RBID : PMC:4528193

Abstract

We examined the local adaptation patterns in a system comprising several interconnected heterogeneous plant populations from which populations of two phylogenetically closely related pathogens were also sampled. The host is Hordeum vulgare (cultivated barley); the pathogens are Pyrenophora teres f. teres (net form) and Pyrenophora teres f. maculata (spot form), the causal agents of barley net blotch. We integrated two approaches, the comparison between the population structures of the host and the pathogens, and a cross-inoculation test. We demonstrated that two closely related pathogens with very similar niche specialisation and life-styles can give rise to different co-evolutionary outcomes on the same host. Indeed, we detected local adaptation for the net form of the pathogen but not for the spot form. We also provided evidence that an a-priori well-known resistance quantitative-trait-locus on barley chromosome 6H is involved in the co-evolutionary ‘arms race’ between the plant and the net-form pathogen. Moreover, data suggested latitudinal clines of host resistance and that different ecological conditions can result in differential selective pressures at different sites. Our data are of interest for on-farm conservation of plant genetic resources, as also in establishing efficient breeding programs and strategies for deployment of resistance genes of P. teres.


Url:
DOI: 10.1038/srep12834
PubMed: 26248796
PubMed Central: 4528193

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PMC:4528193

Le document en format XML

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<p>We examined the local adaptation patterns in a system comprising several interconnected heterogeneous plant populations from which populations of two phylogenetically closely related pathogens were also sampled. The host is
<italic>Hordeum vulgare</italic>
(cultivated barley); the pathogens are
<italic>Pyrenophora teres</italic>
f.
<italic>teres</italic>
(net form) and
<italic>Pyrenophora teres</italic>
f.
<italic>maculata</italic>
(spot form), the causal agents of barley net blotch. We integrated two approaches, the comparison between the population structures of the host and the pathogens, and a cross-inoculation test. We demonstrated that two closely related pathogens with very similar niche specialisation and life-styles can give rise to different co-evolutionary outcomes on the same host. Indeed, we detected local adaptation for the net form of the pathogen but not for the spot form. We also provided evidence that an
<italic>a-priori</italic>
well-known resistance quantitative-trait-locus on barley chromosome 6H is involved in the co-evolutionary ‘arms race’ between the plant and the net-form pathogen. Moreover, data suggested latitudinal clines of host resistance and that different ecological conditions can result in differential selective pressures at different sites. Our data are of interest for
<italic>on-farm</italic>
conservation of plant genetic resources, as also in establishing efficient breeding programs and strategies for deployment of resistance genes of
<italic>P. teres</italic>
.</p>
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</TEI>
<pmc article-type="research-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Sci Rep</journal-id>
<journal-id journal-id-type="iso-abbrev">Sci Rep</journal-id>
<journal-title-group>
<journal-title>Scientific Reports</journal-title>
</journal-title-group>
<issn pub-type="epub">2045-2322</issn>
<publisher>
<publisher-name>Nature Publishing Group</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">26248796</article-id>
<article-id pub-id-type="pmc">4528193</article-id>
<article-id pub-id-type="pii">srep12834</article-id>
<article-id pub-id-type="doi">10.1038/srep12834</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Co-evolution in a landrace meta-population: two closely related pathogens interacting with the same host can lead to different adaptive outcomes</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Rau</surname>
<given-names>Domenico</given-names>
</name>
<xref ref-type="corresp" rid="c1">a</xref>
<xref ref-type="aff" rid="a1">1</xref>
<xref ref-type="author-notes" rid="n1">*</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Rodriguez</surname>
<given-names>Monica</given-names>
</name>
<xref ref-type="aff" rid="a1">1</xref>
<xref ref-type="author-notes" rid="n1">*</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Leonarda Murgia</surname>
<given-names>Maria</given-names>
</name>
<xref ref-type="aff" rid="a1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Balmas</surname>
<given-names>Virgilio</given-names>
</name>
<xref ref-type="aff" rid="a2">2</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bitocchi</surname>
<given-names>Elena</given-names>
</name>
<xref ref-type="aff" rid="a3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bellucci</surname>
<given-names>Elisa</given-names>
</name>
<xref ref-type="aff" rid="a3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Nanni</surname>
<given-names>Laura</given-names>
</name>
<xref ref-type="aff" rid="a3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Attene</surname>
<given-names>Giovanna</given-names>
</name>
<xref ref-type="aff" rid="a1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Papa</surname>
<given-names>Roberto</given-names>
</name>
<xref ref-type="aff" rid="a3">3</xref>
</contrib>
<aff id="a1">
<label>1</label>
<institution>Sezione di Agronomia, Coltivazioni Erbacee e Genetica, Dipartimento di Agraria, Università degli Studi di Sassari</institution>
, Sassari,
<country>Italy</country>
</aff>
<aff id="a2">
<label>2</label>
<institution>Sezione di Patologia Vegetale ed Entomologia, Dipartimento di Agraria, Università degli Studi di Sassari</institution>
, Sassari,
<country>Italy</country>
</aff>
<aff id="a3">
<label>3</label>
<institution>Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche</institution>
, Ancona,
<country>Italy</country>
</aff>
</contrib-group>
<author-notes>
<corresp id="c1">
<label>a</label>
<email>dmrau@uniss.it</email>
</corresp>
<fn id="n1">
<label>*</label>
<p>These authors contributed equally to this work.</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>07</day>
<month>08</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="collection">
<year>2015</year>
</pub-date>
<volume>5</volume>
<elocation-id>12834</elocation-id>
<history>
<date date-type="received">
<day>10</day>
<month>12</month>
<year>2014</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>06</month>
<year>2015</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright © 2015, Macmillan Publishers Limited</copyright-statement>
<copyright-year>2015</copyright-year>
<copyright-holder>Macmillan Publishers Limited</copyright-holder>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<pmc-comment>author-paid</pmc-comment>
<license-p>This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
</license-p>
</license>
</permissions>
<abstract>
<p>We examined the local adaptation patterns in a system comprising several interconnected heterogeneous plant populations from which populations of two phylogenetically closely related pathogens were also sampled. The host is
<italic>Hordeum vulgare</italic>
(cultivated barley); the pathogens are
<italic>Pyrenophora teres</italic>
f.
<italic>teres</italic>
(net form) and
<italic>Pyrenophora teres</italic>
f.
<italic>maculata</italic>
(spot form), the causal agents of barley net blotch. We integrated two approaches, the comparison between the population structures of the host and the pathogens, and a cross-inoculation test. We demonstrated that two closely related pathogens with very similar niche specialisation and life-styles can give rise to different co-evolutionary outcomes on the same host. Indeed, we detected local adaptation for the net form of the pathogen but not for the spot form. We also provided evidence that an
<italic>a-priori</italic>
well-known resistance quantitative-trait-locus on barley chromosome 6H is involved in the co-evolutionary ‘arms race’ between the plant and the net-form pathogen. Moreover, data suggested latitudinal clines of host resistance and that different ecological conditions can result in differential selective pressures at different sites. Our data are of interest for
<italic>on-farm</italic>
conservation of plant genetic resources, as also in establishing efficient breeding programs and strategies for deployment of resistance genes of
<italic>P. teres</italic>
.</p>
</abstract>
</article-meta>
</front>
<floats-group>
<fig id="f1">
<label>Figure 1</label>
<caption>
<title>Correlations (Pearson’s ‘r’) between pathogen and host population gene diversity (Nei, 1978).</title>
<p>The significance of each correlation is based on the Spearman-rank non-parametric method. Calculations were performed for the
<italic>Ptt</italic>
(red) and
<italic>Ptm</italic>
(green) separately, and using all of the markers, only the putatively neutral markers, or the markers putatively under divergent selection.</p>
</caption>
<graphic xlink:href="srep12834-f1"></graphic>
</fig>
<fig id="f2">
<label>Figure 2</label>
<caption>
<title>Interactions for the pathogen
<italic>forma specialis</italic>
 × plant population.</title>
<p>(
<bold>A</bold>
) Level of resistance (pathogen aggressivity) that are not connected by the same letters are different, with P < 0.05 based on Tukey-Kramer tests. (
<bold>B</bold>
) Differences (%) between the performance of the
<italic>Ptt</italic>
and the
<italic>Ptm</italic>
on the same host population.</p>
</caption>
<graphic xlink:href="srep12834-f2"></graphic>
</fig>
<fig id="f3">
<label>Figure 3</label>
<caption>
<title>Correlation between size of the necrotic lesions produced by
<italic>Ptt</italic>
and
<italic>Ptm</italic>
across the 36 barley lines considered in the present study.</title>
<p>The density ellipse (α = 0.95) is also drawn.</p>
</caption>
<graphic xlink:href="srep12834-f3"></graphic>
</fig>
<fig id="f4">
<label>Figure 4</label>
<caption>
<title>Correlation between size of the necrotic lesions on the barley lines and latitude of provenance.</title>
<p>Calculations are given separately for the
<italic>Ptt</italic>
(top) and the
<italic>Ptm</italic>
(bottom) of
<italic>P. teres</italic>
.</p>
</caption>
<graphic xlink:href="srep12834-f4"></graphic>
</fig>
<fig id="f5">
<label>Figure 5</label>
<caption>
<title>Mean size of the necrotic lesions produced by
<italic>Ptt</italic>
and
<italic>Ptm</italic>
</title>
<p>(
<bold>A</bold>
), and separately for the Sympatric (
<italic>sym</italic>
)
<italic>versus</italic>
Allopatric (
<italic>allo</italic>
) population combination within the
<italic>Ptt</italic>
and the
<italic>Ptm</italic>
form (
<bold>B</bold>
).</p>
</caption>
<graphic xlink:href="srep12834-f5"></graphic>
</fig>
<fig id="f6">
<label>Figure 6</label>
<caption>
<title>Correlations between the strength of local adaptation of the
<italic>Ptt</italic>
pathogen and the genetic (F
<sub>ST</sub>
) and geographic (km) distances between the populations.</title>
<p>For each pair of populations, local adaptation was measured by the differences in the sympatric–allopatric comparison using the population least square mean calculated by applying the statistical model in
<xref ref-type="table" rid="t4">Table 4</xref>
. Genetic distances between the pathogen populations are based on AFLPs (
<bold>A</bold>
), and those among the host populations are based on SSAPs (
<bold>B</bold>
). For each correlation, we report the coefficient of correlation (r), while the P values were determined by the Spearman-rank non-parametric method.</p>
</caption>
<graphic xlink:href="srep12834-f6"></graphic>
</fig>
<fig id="f7">
<label>Figure 7</label>
<caption>
<title>Distribution of the five alleles found at Bmag0009 SSR locus within and among the six Sardinian barley landrace populations.</title>
<p>On the right part of the figure it is reported the average size of the necrosis (in pixels) for each of the five alleles. Means that do not share the same letter are different (P < 0.05) based on Tukey-Kramer HD test.</p>
</caption>
<graphic xlink:href="srep12834-f7"></graphic>
</fig>
<fig id="f8">
<label>Figure 8</label>
<caption>
<title>Associations between the
<italic>Ptt</italic>
population structure and the population divergence (F
<sub>ST</sub>
) at the Bmag0009 locus (associated to a QTL for
<italic>Ptt</italic>
resistance) and all of the SSAPs (A, B), and between the
<italic>Ptt</italic>
local adaptation and the F
<sub>ST</sub>
at the Bmag0009 locus (C). The significance of each correlation is based on the Spearman-rank non-parametric method.</title>
</caption>
<graphic xlink:href="srep12834-f8"></graphic>
</fig>
<fig id="f9">
<label>Figure 9</label>
<caption>
<title>Map of the island of Sardinia, showing the six sites where the plants and pathogen samples were collected.</title>
<p>Altimetric information is represented in a simplified way; the map was drawn by the first author of the article (D. Rau) using the drawing tools of Microsoft PowerPoint 2010.</p>
</caption>
<graphic xlink:href="srep12834-f9"></graphic>
</fig>
<fig id="f10">
<label>Figure 10</label>
<caption>
<title>Determination of the area of the necrotic lesions produced by
<italic>P. teres</italic>
on the barley leaves.</title>
<p>(
<bold>A</bold>
) Each necrotic lesion was cut and (
<bold>B</bold>
) a collection of necrotic lesions was obtained. As an example, each circle in (
<bold>B</bold>
) includes the necrotic lesion collected for a host and pathogen combination; nine combinations are represented.</p>
</caption>
<graphic xlink:href="srep12834-f10"></graphic>
</fig>
<table-wrap position="float" id="t1">
<label>Table 1</label>
<caption>
<title>Results of the two-way and three-way Mantel tests that show correlations (
<italic>r</italic>
) and partial correlations between the genetic distances among the pathogen populations
<italic>versus</italic>
the host population genetic distances and geographical distances among sites.</title>
</caption>
<table frame="hsides" rules="groups" border="1">
<colgroup>
<col align="left"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
</colgroup>
<thead valign="bottom">
<tr>
<th colspan="2" align="left" valign="top" charoff="50">Datasets and variables</th>
<th align="center" valign="top" charoff="50">Correlation (r)</th>
<th align="center" valign="top" charoff="50">P</th>
<th align="center" valign="top" charoff="50">Partial correlation</th>
<th align="center" valign="top" charoff="50">P</th>
<th align="center" valign="top" charoff="50">Explained variance (%)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="7" align="left" valign="top" charoff="50">All markers</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic> Ptt</italic>
pathogen
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Barley host</td>
<td align="center" valign="top" charoff="50">0.586</td>
<td align="center" valign="top" charoff="50">
<bold>0.0107</bold>
</td>
<td align="center" valign="top" charoff="50">0.597</td>
<td align="center" valign="top" charoff="50">
<bold>0.0084</bold>
</td>
<td align="center" valign="top" charoff="50">25.8</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.700</td>
<td align="center" valign="top" charoff="50">0.0725</td>
<td align="center" valign="top" charoff="50">0.707</td>
<td align="center" valign="top" charoff="50">0.0592</td>
<td align="center" valign="top" charoff="50">41.4</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic></italic>
Barley
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.246</td>
<td align="center" valign="top" charoff="50">0.6134</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic> Ptm</italic>
pathogen
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Barley host</td>
<td align="center" valign="top" charoff="50">−0.079</td>
<td align="center" valign="top" charoff="50">0.5770</td>
<td align="center" valign="top" charoff="50">−0.186</td>
<td align="center" valign="top" charoff="50">0.6381</td>
<td align="center" valign="top" charoff="50">1.59</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.200</td>
<td align="center" valign="top" charoff="50">0.3060</td>
<td align="center" valign="top" charoff="50">0.260</td>
<td align="center" valign="top" charoff="50">0.2162</td>
<td align="center" valign="top" charoff="50">5.75</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic></italic>
Barley
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.431</td>
<td align="center" valign="top" charoff="50">0.2556</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
<tr>
<td colspan="7" align="left" valign="top" charoff="50">Putatively neutral</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic> Ptt</italic>
pathogen
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Barley host</td>
<td align="center" valign="top" charoff="50">0.584</td>
<td align="center" valign="top" charoff="50">
<bold>0.0297</bold>
</td>
<td align="center" valign="top" charoff="50">0.543</td>
<td align="center" valign="top" charoff="50">0.0570</td>
<td align="center" valign="top" charoff="50">25.3</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.644</td>
<td align="center" valign="top" charoff="50">0.0778</td>
<td align="center" valign="top" charoff="50">0.611</td>
<td align="center" valign="top" charoff="50">0.0756</td>
<td align="center" valign="top" charoff="50">33.3</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic></italic>
Barley
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.289</td>
<td align="center" valign="top" charoff="50">0.6301</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic> Ptm</italic>
pathogen
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Barley host</td>
<td align="center" valign="top" charoff="50">0.258</td>
<td align="center" valign="top" charoff="50">0.3008</td>
<td align="center" valign="top" charoff="50">0.312</td>
<td align="center" valign="top" charoff="50">0.2082</td>
<td align="center" valign="top" charoff="50">9.31</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">−0.022</td>
<td align="center" valign="top" charoff="50">0.5439</td>
<td align="center" valign="top" charoff="50">−0.183</td>
<td align="center" valign="top" charoff="50">0.6267</td>
<td align="center" valign="top" charoff="50">0.05</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic></italic>
Barley
<italic>v</italic>
s.</td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.431</td>
<td align="center" valign="top" charoff="50">0.2501</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
<tr>
<td colspan="7" align="left" valign="top" charoff="50">Putatively under selection</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic> Ptt</italic>
pathogen
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Barley host</td>
<td align="center" valign="top" charoff="50">0.414</td>
<td align="center" valign="top" charoff="50">
<bold>0.0041</bold>
</td>
<td align="center" valign="top" charoff="50">0.443</td>
<td align="center" valign="top" charoff="50">
<bold>0.0028</bold>
</td>
<td align="center" valign="top" charoff="50">14.7</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.603</td>
<td align="center" valign="top" charoff="50">0.0555</td>
<td align="center" valign="top" charoff="50">0.618</td>
<td align="center" valign="top" charoff="50">0.0555</td>
<td align="center" valign="top" charoff="50">34.7</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic></italic>
Barley
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.246</td>
<td align="center" valign="top" charoff="50">0.6230</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic> Ptm</italic>
pathogen
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Barley host</td>
<td align="center" valign="top" charoff="50">−0.051</td>
<td align="center" valign="top" charoff="50">0.4681</td>
<td align="center" valign="top" charoff="50">−0.021</td>
<td align="center" valign="top" charoff="50">0.4333</td>
<td align="center" valign="top" charoff="50">0.10</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">−0.299</td>
<td align="center" valign="top" charoff="50">0.7171</td>
<td align="center" valign="top" charoff="50">−0.296</td>
<td align="center" valign="top" charoff="50">0.7173</td>
<td align="center" valign="top" charoff="50">8.90</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic></italic>
Barley
<italic>vs.</italic>
</td>
<td align="center" valign="top" charoff="50">Geography</td>
<td align="center" valign="top" charoff="50">0.101</td>
<td align="center" valign="top" charoff="50">0.5703</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t1-fn1">
<p>The significance of r was tested using 100,000 permutations.
<bold>Bold</bold>
, significant correlations. Data are presented for the
<italic>Ptt</italic>
and
<italic>Ptm</italic>
forms of the pathogen separately, and using all of the SSAP markers, and only the putatively neutral and putatively under divergence selection markers.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="t2">
<label>Table 2</label>
<caption>
<title>Mean population divergence estimates (F
<sub>ST</sub>
) for the barley host (SSAP) and for the
<italic>Ptt</italic>
and
<italic>Ptm</italic>
pathogen (AFLP) populations.</title>
</caption>
<table frame="hsides" rules="groups" border="1">
<colgroup>
<col align="left"></col>
<col align="left"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
</colgroup>
<thead valign="bottom">
<tr>
<th align="left" valign="top" charoff="50">Dataset</th>
<th align="center" valign="top" charoff="50">Organism</th>
<th align="center" valign="top" charoff="50">Mean F
<sub>ST</sub>
<xref ref-type="fn" rid="t2-fn1">(1)</xref>
</th>
<th align="center" valign="top" charoff="50">95% confidence interval</th>
<th align="center" valign="top" charoff="50">Nm
<sub>isl</sub>
</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left" valign="top" charoff="50">All markers</td>
<td align="left" valign="top" charoff="50">
<italic>Ptt</italic>
</td>
<td align="center" valign="top" charoff="50">0.276 (a)</td>
<td align="center" valign="top" charoff="50">0.201–0.351</td>
<td align="center" valign="top" charoff="50">1.312</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="left" valign="top" charoff="50">Barley</td>
<td align="center" valign="top" charoff="50">0.189 (b)</td>
<td align="center" valign="top" charoff="50">0.156–0.223</td>
<td align="center" valign="top" charoff="50">2.146</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="left" valign="top" charoff="50">
<italic>Ptm</italic>
</td>
<td align="center" valign="top" charoff="50">0.071 (c)</td>
<td align="center" valign="top" charoff="50">0.047–0.095</td>
<td align="center" valign="top" charoff="50">6.542</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">‘Neutral’</td>
<td align="left" valign="top" charoff="50">
<italic>Ptt</italic>
</td>
<td align="center" valign="top" charoff="50">0.221 (a)</td>
<td align="center" valign="top" charoff="50">0.156–0.292</td>
<td align="center" valign="top" charoff="50">1.76</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="left" valign="top" charoff="50">Barley</td>
<td align="center" valign="top" charoff="50">0.157 (b)</td>
<td align="center" valign="top" charoff="50">0.133–0.181</td>
<td align="center" valign="top" charoff="50">2.68</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50"> </td>
<td align="left" valign="top" charoff="50">
<italic>Ptm</italic>
</td>
<td align="center" valign="top" charoff="50">0.059 (c)</td>
<td align="center" valign="top" charoff="50">0.039–0.078</td>
<td align="center" valign="top" charoff="50">7.97</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t2-fn1">
<p>Letters between parentheses indicate F
<sub>ST</sub>
means that are separated with P < 0.05 based on the Tukey-Kramer tests (for this calculation, the negative F
<sub>ST</sub>
were set to zero). The F
<sub>ST</sub>
95% confidence intervals are from the bootstrap over the loci (10,000 replications). Nm
<sub>isl</sub>
 = migration rate assuming an island model of population structure.</p>
</fn>
<fn id="t2-fn2">
<p>
<sup>(1)</sup>
All F
<sub>ST</sub>
were significant at the permutation tests, with P between <10
<sup>−3</sup>
and <10
<sup>−5</sup>
.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="t3">
<label>Table 3</label>
<caption>
<title>ANOVA illustrating the effects of the
<italic>Ptt</italic>
and
<italic>Ptm</italic>
pathogens, the barley host population, and the
<italic>forma specialis</italic>
 × host population on necrosis size. d.f. = degrees of freedom; SS = sum of squares; F = F ratio.</title>
</caption>
<table frame="hsides" rules="groups" border="1">
<colgroup>
<col align="left"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
</colgroup>
<thead valign="bottom">
<tr>
<th align="left" valign="top" charoff="50">Source</th>
<th align="center" valign="top" charoff="50">d.f.</th>
<th align="center" valign="top" charoff="50">SS</th>
<th align="center" valign="top" charoff="50">F ratio</th>
<th align="center" valign="top" charoff="50">Probability</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left" valign="top" charoff="50">
<italic>Forma specialis</italic>
</td>
<td align="center" valign="top" charoff="50">1</td>
<td align="center" valign="top" charoff="50">209885.2</td>
<td align="center" valign="top" charoff="50">127.5</td>
<td align="center" valign="top" charoff="50"><0.0001</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">Host population</td>
<td align="center" valign="top" charoff="50">5</td>
<td align="center" valign="top" charoff="50">612920.5</td>
<td align="center" valign="top" charoff="50">74.5</td>
<td align="center" valign="top" charoff="50"><0.0001</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">
<italic>Forma</italic>
 × host population</td>
<td align="center" valign="top" charoff="50">5</td>
<td align="center" valign="top" charoff="50">79578.2</td>
<td align="center" valign="top" charoff="50">9.7</td>
<td align="center" valign="top" charoff="50"><0.0001</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">Error</td>
<td align="center" valign="top" charoff="50">6715</td>
<td align="center" valign="top" charoff="50">11052804</td>
<td align="center" valign="top" charoff="50">1646</td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap position="float" id="t4">
<label>Table 4</label>
<caption>
<title>Results of the analysis of variance of the infection data for the
<italic>Ptt</italic>
and
<italic>Ptm</italic>
separately.</title>
</caption>
<table frame="hsides" rules="groups" border="1">
<colgroup>
<col align="left"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
</colgroup>
<thead valign="bottom">
<tr>
<th rowspan="2" align="left" valign="bottom" charoff="50">Source</th>
<th colspan="4" align="center" valign="top" charoff="50">
<italic>Ptt</italic>
<hr></hr>
</th>
<th colspan="4" align="center" valign="top" charoff="50">
<italic>Ptm</italic>
<hr></hr>
</th>
</tr>
<tr>
<th align="center" valign="top" charoff="50">
<italic>d.f.</italic>
</th>
<th align="center" valign="top" charoff="50">SS</th>
<th align="center" valign="top" charoff="50">F</th>
<th align="center" valign="top" charoff="50">Probability</th>
<th align="center" valign="top" charoff="50">
<italic>d.f.</italic>
</th>
<th align="center" valign="top" charoff="50">SS</th>
<th align="center" valign="top" charoff="50">F</th>
<th align="center" valign="top" charoff="50">Probability</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left" valign="top" charoff="50">Host pop
<xref ref-type="fn" rid="t4-fn1">(1)</xref>
</td>
<td align="center" valign="top" charoff="50">4</td>
<td align="center" valign="top" charoff="50">193309.0</td>
<td align="center" valign="top" charoff="50">25.08</td>
<td align="center" valign="top" charoff="50"><0.0001</td>
<td align="center" valign="top" charoff="50">4</td>
<td align="center" valign="top" charoff="50">210156.2</td>
<td align="center" valign="top" charoff="50">62.65</td>
<td align="center" valign="top" charoff="50"><0.0001</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">Pathogen pop
<xref ref-type="fn" rid="t4-fn1">(1)</xref>
</td>
<td align="center" valign="top" charoff="50">4</td>
<td align="center" valign="top" charoff="50">1106076.7</td>
<td align="center" valign="top" charoff="50">143.51</td>
<td align="center" valign="top" charoff="50"><0.0001</td>
<td align="center" valign="top" charoff="50">4</td>
<td align="center" valign="top" charoff="50">580584.3</td>
<td align="center" valign="top" charoff="50">173.07</td>
<td align="center" valign="top" charoff="50"><0.0001</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">Sympatric
<italic>versus</italic>
allopatric
<xref ref-type="fn" rid="t4-fn2">(2)</xref>
</td>
<td align="center" valign="top" charoff="50">1</td>
<td align="center" valign="top" charoff="50">19885.6</td>
<td align="center" valign="top" charoff="50">5.62</td>
<td align="char" valign="top" char="." charoff="50">0.0285</td>
<td align="center" valign="top" charoff="50">1</td>
<td align="center" valign="top" charoff="50">8.8</td>
<td align="center" valign="top" charoff="50">0.01</td>
<td align="char" valign="top" char="." charoff="50">0.9300</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">Host pop. xpath. pop. remainder
<xref ref-type="fn" rid="t4-fn1">(1)</xref>
</td>
<td align="center" valign="top" charoff="50">19</td>
<td align="center" valign="top" charoff="50">67255.0</td>
<td align="center" valign="top" charoff="50">1.84</td>
<td align="char" valign="top" char="." charoff="50">0.0147</td>
<td align="center" valign="top" charoff="50">19</td>
<td align="center" valign="top" charoff="50">19650.9</td>
<td align="center" valign="top" charoff="50">1.23</td>
<td align="char" valign="top" char="." charoff="50">0.2198</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">Error</td>
<td align="center" valign="top" charoff="50">3362</td>
<td align="center" valign="top" charoff="50">6477994.9</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50">3305</td>
<td align="center" valign="top" charoff="50">2771770.9</td>
<td align="center" valign="top" charoff="50"> </td>
<td align="center" valign="top" charoff="50"> </td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t4-fn1">
<p>For this analysis, all of the host populations were retained; i.e., for both the
<italic>Ptt</italic>
and the
<italic>Ptm</italic>
of the pathogen, we considered six host populations. For the
<italic>Ptt</italic>
, the host population COR do not have the corresponding pathogen population, while for the
<italic>Ptm</italic>
the host population STU do not have the corresponding pathogen population. d.f. = degrees of freedom; SS = sum of squares; F = F ratio.</p>
</fn>
<fn id="t4-fn2">
<p>
<sup>(1)</sup>
Tested for error variance.</p>
</fn>
<fn id="t4-fn3">
<p>
<sup>(2)</sup>
Tested for the remainder of the host population × the remainder of the pathogen population.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="t5">
<label>Table 5</label>
<caption>
<title>Results of the jack-knifing over the populations.</title>
</caption>
<table frame="hsides" rules="groups" border="1">
<colgroup>
<col align="left"></col>
<col align="center"></col>
<col align="center"></col>
</colgroup>
<thead valign="bottom">
<tr>
<th rowspan="2" align="left" valign="bottom" charoff="50">Eliminated population</th>
<th colspan="2" align="center" valign="top" charoff="50">Sympatric
<italic>versus</italic>
Allopatric
<hr></hr>
</th>
</tr>
<tr>
<th align="center" valign="top" charoff="50">F</th>
<th align="center" valign="top" charoff="50">P</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left" valign="top" charoff="50">CUM</td>
<td align="center" valign="top" charoff="50">1.92</td>
<td align="center" valign="top" charoff="50">0.194</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">STU</td>
<td align="center" valign="top" charoff="50">2.81</td>
<td align="center" valign="top" charoff="50">0.122</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">PIR</td>
<td align="center" valign="top" charoff="50">5.01</td>
<td align="center" valign="top" charoff="50">0.047</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">TER</td>
<td align="center" valign="top" charoff="50">5.42</td>
<td align="center" valign="top" charoff="50">0.040</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">NXM</td>
<td align="center" valign="top" charoff="50">5.68</td>
<td align="center" valign="top" charoff="50">0.036</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t5-fn1">
<p>The same model as in
<xref ref-type="table" rid="t5">Table 5</xref>
was applied while sequentially eliminating each host population, to determine the P value for the Sympatric
<italic>versus</italic>
Allopatric term for the
<italic>Ptt</italic>
pathogen. This analysis was performed considering all six of the host populations (i.e., including COR, for which no pathogen sample was available). The populations are in descending order based on their ‘weight’ on the P value for the Sympatric
<italic>versus</italic>
Allopatric term.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="t6">
<label>Table 6</label>
<caption>
<title>Codes and sample sizes of the host (barley) and pathogen (barley net blotch) samples.</title>
</caption>
<table frame="hsides" rules="groups" border="1">
<colgroup>
<col align="left"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
<col align="center"></col>
</colgroup>
<thead valign="bottom">
<tr>
<th colspan="3" align="center" valign="top" charoff="50">Host population sample
<xref ref-type="fn" rid="t6-fn1">(1)</xref>
<hr></hr>
</th>
<th colspan="3" align="center" valign="top" charoff="50">Corresponding pathogen sample
<xref ref-type="fn" rid="t6-fn2">(2)</xref>
<hr></hr>
</th>
</tr>
<tr>
<th align="left" valign="top" charoff="50">Code</th>
<th align="center" valign="top" charoff="50">Number of lines characterised by SSAP
<xref ref-type="fn" rid="t6-fn1">(1)</xref>
</th>
<th align="center" valign="top" charoff="50">Number of lines in the cross-inoculation (same for Ptt and Ptm)</th>
<th align="center" valign="top" charoff="50">Code</th>
<th align="center" valign="top" charoff="50">Number of isolates characterised by AFLP (Ptt, Ptm)
<xref ref-type="fn" rid="t6-fn2">(2)</xref>
</th>
<th align="center" valign="top" charoff="50">Number of isolates in the cross-inoculation (Ptt, Ptm)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left" valign="top" charoff="50">CUM</td>
<td align="center" valign="top" charoff="50">33</td>
<td align="center" valign="top" charoff="50">6</td>
<td align="center" valign="top" charoff="50">SEC</td>
<td align="center" valign="top" charoff="50">31 (2,29)</td>
<td align="center" valign="top" charoff="50">2, 4</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">PIR</td>
<td align="center" valign="top" charoff="50">33</td>
<td align="center" valign="top" charoff="50">6</td>
<td align="center" valign="top" charoff="50">PIR</td>
<td align="center" valign="top" charoff="50">24 (16,8)</td>
<td align="center" valign="top" charoff="50">5, 4</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">SOR</td>
<td align="center" valign="top" charoff="50">32</td>
<td align="center" valign="top" charoff="50">6</td>
<td align="center" valign="top" charoff="50">TER</td>
<td align="center" valign="top" charoff="50">26 (6,20)</td>
<td align="center" valign="top" charoff="50">3, 4</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">NXM</td>
<td align="center" valign="top" charoff="50">31</td>
<td align="center" valign="top" charoff="50">6</td>
<td align="center" valign="top" charoff="50">SIR</td>
<td align="center" valign="top" charoff="50">21 (3, 18)</td>
<td align="center" valign="top" charoff="50">1, 4</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">STU</td>
<td align="center" valign="top" charoff="50">30</td>
<td align="center" valign="top" charoff="50">6</td>
<td align="center" valign="top" charoff="50">BAC</td>
<td align="center" valign="top" charoff="50">36 (36,0)</td>
<td align="center" valign="top" charoff="50">6, 0</td>
</tr>
<tr>
<td align="left" valign="top" charoff="50">COR</td>
<td align="center" valign="top" charoff="50">30</td>
<td align="center" valign="top" charoff="50">6</td>
<td align="center" valign="top" charoff="50">SES</td>
<td align="center" valign="top" charoff="50">12 (5, 7)</td>
<td align="center" valign="top" charoff="50">0, 1</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t6-fn1">
<p>
<sup>(1)</sup>
Based on Rodriguez
<italic>et al.</italic>
2012
<xref ref-type="bibr" rid="b25">25</xref>
.</p>
</fn>
<fn id="t6-fn2">
<p>
<sup>(2)</sup>
Based on Rau
<italic>et al.</italic>
2003
<xref ref-type="bibr" rid="b31">31</xref>
.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</pmc>
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