Signatures of Purifying and Local Positive Selection in Human miRNAs
Identifieur interne : 000423 ( Pmc/Corpus ); précédent : 000422; suivant : 000424Signatures of Purifying and Local Positive Selection in Human miRNAs
Auteurs : Hélène Quach ; Luis B. Barreiro ; Guillaume Laval ; Nora Zidane ; Etienne Patin ; Kenneth K. Kidd ; Judith R. Kidd ; Christiane Bouchier ; Michel Veuille ; Christophe Antoniewski ; Lluís Quintana-MurciSource :
- American Journal of Human Genetics [ 0002-9297 ] ; 2009.
Abstract
MicroRNAs (miRNAs) are noncoding RNAs involved in posttranscriptional gene repression, and their role in diverse physiological processes is increasingly recognized. Yet, few efforts have been devoted to evolutionary studies of human miRNAs. Knowledge about the way in which natural selection has targeted miRNAs should provide insight into their functional relevance as well as their mechanisms of action. Here we used miRNAs as a model system for investigating the influence of natural selection on gene regulation by characterizing the full spectrum of naturally occurring sequence variation of 117 human miRNAs from different populations worldwide. We found that purifying selection has globally constrained the diversity of miRNA-containing regions and has strongly targeted the mature miRNA. This observation emphasizes that mutations in these molecules are likely to be deleterious, and therefore they can have severe phenotypic consequences on human health. More importantly, we obtained evidence of population-specific events of positive selection acting on a number of miRNA-containing regions. Notably, our analysis revealed that positive selection has targeted a “small-RNA-rich island” on chromosome 14, harboring both miRNAs and small nucleolar RNAs, in Europeans and East Asians. These observations support the notion that the tuning of gene expression contributes to the processes by which populations adapt to specific environments. These findings will fuel future investigations exploring how genetic and functional variation of miRNAs under selection affects the repression of their mRNA targets, increasing our understanding of the role of gene regulation in population adaptation and human disease.
Url:
DOI: 10.1016/j.ajhg.2009.01.022
PubMed: 19232555
PubMed Central: 2667980
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PMC:2667980Le document en format XML
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Signatures of Purifying and Local Positive Selection in Human miRNAs</title>
<author><name sortKey="Quach, Helene" sort="Quach, Helene" uniqKey="Quach H" first="Hélène" last="Quach">Hélène Quach</name>
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<author><name sortKey="Barreiro, Luis B" sort="Barreiro, Luis B" uniqKey="Barreiro L" first="Luis B." last="Barreiro">Luis B. Barreiro</name>
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<author><name sortKey="Laval, Guillaume" sort="Laval, Guillaume" uniqKey="Laval G" first="Guillaume" last="Laval">Guillaume Laval</name>
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<author><name sortKey="Zidane, Nora" sort="Zidane, Nora" uniqKey="Zidane N" first="Nora" last="Zidane">Nora Zidane</name>
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<author><name sortKey="Patin, Etienne" sort="Patin, Etienne" uniqKey="Patin E" first="Etienne" last="Patin">Etienne Patin</name>
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<author><name sortKey="Bouchier, Christiane" sort="Bouchier, Christiane" uniqKey="Bouchier C" first="Christiane" last="Bouchier">Christiane Bouchier</name>
<affiliation><nlm:aff id="aff2"></nlm:aff>
</affiliation>
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<author><name sortKey="Veuille, Michel" sort="Veuille, Michel" uniqKey="Veuille M" first="Michel" last="Veuille">Michel Veuille</name>
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<author><name sortKey="Antoniewski, Christophe" sort="Antoniewski, Christophe" uniqKey="Antoniewski C" first="Christophe" last="Antoniewski">Christophe Antoniewski</name>
<affiliation><nlm:aff id="aff5"></nlm:aff>
</affiliation>
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<author><name sortKey="Quintana Murci, Lluis" sort="Quintana Murci, Lluis" uniqKey="Quintana Murci L" first="Lluís" last="Quintana-Murci">Lluís Quintana-Murci</name>
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<series><title level="j">American Journal of Human Genetics</title>
<idno type="ISSN">0002-9297</idno>
<idno type="eISSN">1537-6605</idno>
<imprint><date when="2009">2009</date>
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<front><div type="abstract" xml:lang="en"><p>MicroRNAs (miRNAs) are noncoding RNAs involved in posttranscriptional gene repression, and their role in diverse physiological processes is increasingly recognized. Yet, few efforts have been devoted to evolutionary studies of human miRNAs. Knowledge about the way in which natural selection has targeted miRNAs should provide insight into their functional relevance as well as their mechanisms of action. Here we used miRNAs as a model system for investigating the influence of natural selection on gene regulation by characterizing the full spectrum of naturally occurring sequence variation of 117 human miRNAs from different populations worldwide. We found that purifying selection has globally constrained the diversity of miRNA-containing regions and has strongly targeted the mature miRNA. This observation emphasizes that mutations in these molecules are likely to be deleterious, and therefore they can have severe phenotypic consequences on human health. More importantly, we obtained evidence of population-specific events of positive selection acting on a number of miRNA-containing regions. Notably, our analysis revealed that positive selection has targeted a “small-RNA-rich island” on chromosome 14, harboring both miRNAs and small nucleolar RNAs, in Europeans and East Asians. These observations support the notion that the tuning of gene expression contributes to the processes by which populations adapt to specific environments. These findings will fuel future investigations exploring how genetic and functional variation of miRNAs under selection affects the repression of their mRNA targets, increasing our understanding of the role of gene regulation in population adaptation and human disease.</p>
</div>
</front>
</TEI>
<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Am J Hum Genet</journal-id>
<journal-title>American Journal of Human Genetics</journal-title>
<issn pub-type="ppub">0002-9297</issn>
<issn pub-type="epub">1537-6605</issn>
<publisher><publisher-name>American Society of Human Genetics</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">19232555</article-id>
<article-id pub-id-type="pmc">2667980</article-id>
<article-id pub-id-type="publisher-id">AJHG343</article-id>
<article-id pub-id-type="doi">10.1016/j.ajhg.2009.01.022</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>Signatures of Purifying and Local Positive Selection in Human miRNAs</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Quach</surname>
<given-names>Hélène</given-names>
</name>
<xref rid="aff1" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Barreiro</surname>
<given-names>Luis B.</given-names>
</name>
<xref rid="aff1" ref-type="aff">1</xref>
<xref rid="fn1" ref-type="fn">6</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Laval</surname>
<given-names>Guillaume</given-names>
</name>
<xref rid="aff1" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zidane</surname>
<given-names>Nora</given-names>
</name>
<xref rid="aff2" ref-type="aff">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Patin</surname>
<given-names>Etienne</given-names>
</name>
<xref rid="aff1" ref-type="aff">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kidd</surname>
<given-names>Kenneth K.</given-names>
</name>
<xref rid="aff3" ref-type="aff">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kidd</surname>
<given-names>Judith R.</given-names>
</name>
<xref rid="aff3" ref-type="aff">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Bouchier</surname>
<given-names>Christiane</given-names>
</name>
<xref rid="aff2" ref-type="aff">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Veuille</surname>
<given-names>Michel</given-names>
</name>
<xref rid="aff4" ref-type="aff">4</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Antoniewski</surname>
<given-names>Christophe</given-names>
</name>
<xref rid="aff5" ref-type="aff">5</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Quintana-Murci</surname>
<given-names>Lluís</given-names>
</name>
<email>quintana@pasteur.fr</email>
<xref rid="aff1" ref-type="aff">1</xref>
<xref rid="cor1" ref-type="corresp">∗</xref>
</contrib>
</contrib-group>
<aff id="aff1"><addr-line><sup>1</sup>
Institut Pasteur, Human Evolutionary Genetics, Centre National pour la Recherche Scientifique, URA3012, F-75015, Paris, France</addr-line>
</aff>
<aff id="aff2"><addr-line><sup>2</sup>
Institut Pasteur, Genomics Platform, F-75015, Paris, France</addr-line>
</aff>
<aff id="aff3"><addr-line><sup>3</sup>
Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA</addr-line>
</aff>
<aff id="aff4"><addr-line><sup>4</sup>
Ecole Pratique des Hautes Etudes, UMR 5202, Equipe de génétique des populations, Muséum National d'Histoire Naturelle, F-75005, Paris, France</addr-line>
</aff>
<aff id="aff5"><addr-line><sup>5</sup>
Institut Pasteur, Genetics and Epigenetics of Drosophila, Centre National pour la Recherche Scientifique, URA 2578, F-75015, Paris, France</addr-line>
</aff>
<author-notes><corresp id="cor1"><label>∗</label>
Corresponding author <email>quintana@pasteur.fr</email>
</corresp>
<fn id="fn1"><label>6</label>
<p>Present address: Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA</p>
</fn>
</author-notes>
<pub-date pub-type="ppub"><day>13</day>
<month>3</month>
<year>2009</year>
</pub-date>
<volume>84</volume>
<issue>3</issue>
<fpage>316</fpage>
<lpage>327</lpage>
<history><date date-type="received"><day>10</day>
<month>11</month>
<year>2008</year>
</date>
<date date-type="rev-recd"><day>21</day>
<month>12</month>
<year>2008</year>
</date>
<date date-type="accepted"><day>27</day>
<month>1</month>
<year>2009</year>
</date>
</history>
<permissions><copyright-statement>© 2009 The American Society of Human Genetics. Published by Elsevier Ltd. All right reserved..</copyright-statement>
<copyright-year>2009</copyright-year>
<copyright-holder>The American Society of Human Genetics</copyright-holder>
<license><p>This document may be redistributed and reused, subject to <ext-link ext-link-type="uri" xlink:href="http://www.elsevier.com/wps/find/authorsview.authors/supplementalterms1.0">certain conditions</ext-link>
.</p>
</license>
</permissions>
<abstract><p>MicroRNAs (miRNAs) are noncoding RNAs involved in posttranscriptional gene repression, and their role in diverse physiological processes is increasingly recognized. Yet, few efforts have been devoted to evolutionary studies of human miRNAs. Knowledge about the way in which natural selection has targeted miRNAs should provide insight into their functional relevance as well as their mechanisms of action. Here we used miRNAs as a model system for investigating the influence of natural selection on gene regulation by characterizing the full spectrum of naturally occurring sequence variation of 117 human miRNAs from different populations worldwide. We found that purifying selection has globally constrained the diversity of miRNA-containing regions and has strongly targeted the mature miRNA. This observation emphasizes that mutations in these molecules are likely to be deleterious, and therefore they can have severe phenotypic consequences on human health. More importantly, we obtained evidence of population-specific events of positive selection acting on a number of miRNA-containing regions. Notably, our analysis revealed that positive selection has targeted a “small-RNA-rich island” on chromosome 14, harboring both miRNAs and small nucleolar RNAs, in Europeans and East Asians. These observations support the notion that the tuning of gene expression contributes to the processes by which populations adapt to specific environments. These findings will fuel future investigations exploring how genetic and functional variation of miRNAs under selection affects the repression of their mRNA targets, increasing our understanding of the role of gene regulation in population adaptation and human disease.</p>
</abstract>
</article-meta>
</front>
<floats-wrap><fig id="fig1"><label>Figure 1</label>
<caption><p>miRNA Hairpins Are Selectively Constrained in Human Populations</p>
<p>(A) The miRNA hairpin is composed of the precursor associated with its immediate flanking nucleotides that form a basal stem. The pre-miRNA is composed of an imperfect duplex between the mature miRNA (miR) and its complementary sequence (miR<sup>∗</sup>
), an adjacent stem, and a terminal loop. In our study, the stem refers to the basal stem in addition to the adjacent stem, excluding miR and miR<sup>∗</sup>
. The sizes considered correspond to the empirical mean sizes observed in our dataset for each of these different domains.</p>
<p>(B) Sliding windows of the nucleotide diversity π in miRNA-containing regions. All these regions were aligned on the first nucleotide of the mature miRNA. The window is 87 nt across (the mean size of the miRNA hairpins), with a step size of 1 nt. Each 87 nt window reflects the mean nucleotide diversity across all miRNA-containing regions. The orange line indicates significantly lower-than-expected levels of diversity over the sequenced regions, as determined by the resampling procedure (<xref rid="sec2" ref-type="sec">Material and Methods</xref>
).</p>
<p>(C) Mean SNP density in the various miRNA domains.</p>
<p>(D) Mean nucleotide diversity π of the various miRNA domains. Both the mean SNP density and nucleotide diversity levels were calculated for the actual sizes of each of the different domains within the miRNA hairpins studied. p values were calculated with resampling analyses (<xref rid="sec2" ref-type="sec">Material and Methods</xref>
). NS = non significant.</p>
</caption>
<graphic xlink:href="gr1"></graphic>
</fig>
<fig id="fig2"><label>Figure 2</label>
<caption><p>Sequence-Based Neutrality Tests in the Various Continental Populations Studied</p>
<p>(A) Tajima's <italic>D</italic>
and Fu and Li's <italic>F</italic>
<sup>∗</sup>
in the African (circle), European (triangle), and East Asian (square) samples.</p>
<p>(B) Fay and Wu's <italic>H</italic>
in the African (circle), European (triangle), and East-Asian (square) samples. miRNAs that are significant (p < 0.025 or p > 0.975 for two-sided tests, and p < 0.05 for the one-sided test) under a neutral model with constant population sizes are represented in yellow, and those that are significant after correction for the two demographic models are represented in red.</p>
<p>Nonsignificant regions are shown in gray. Two-sided tests were used for Tajima's <italic>D</italic>
and Fu and Li's <italic>F</italic>
<sup>∗</sup>
, and a one-sided test was used for Fay and Wu's <italic>H</italic>
.</p>
</caption>
<graphic xlink:href="gr2"></graphic>
</fig>
<fig id="fig3"><label>Figure 3</label>
<caption><p>Multiple miRNA Regions Present High Levels of Population Differentiation</p>
<p>The dashed and solid lines correspond to the 95<sup>th</sup>
and 99<sup>th</sup>
percentiles obtained in simulations with our best-fitted demographic model. These thresholds are more stringent (i.e., higher) with respect to the 95<sup>th</sup>
and 99<sup>th</sup>
empirical values of <italic>F</italic>
<sub>ST</sub>
resulting from the resequencing of the 20 noncoding regions (<xref rid="app2" ref-type="sec">Table S8</xref>
).</p>
</caption>
<graphic xlink:href="gr3"></graphic>
</fig>
<fig id="fig4"><label>Figure 4</label>
<caption><p>Recent Positive Selection Targeting a Small-RNA-Rich Island on Chromosome 14</p>
<p>Each line at the bottom of the figure represents a different small RNA; black and red lines denote miRNAs, and gray lines represent snoRNAs. Red lines indicate the miRNAs sequenced in this study.</p>
<p>(A and B) |iHs| values were calculated from HapMap II data for the SNPs genotyped in this region in (A) Asians and (B) Europeans. The dashed lines denote, for each population, the 95<sup>th</sup>
percentile for the empirical value obtained from HapMap II data for chromosome 14. African |iHs| values are not reported because no significant deviation from neutral expectations was observed.</p>
<p>(C) <italic>F</italic>
<sub>ST</sub>
values for pairwise comparisons of Europeans versus Asians. The dashed line denotes the 95<sup>th</sup>
percentile obtained in simulations with our best-fitted demographic model (<xref rid="app2" ref-type="sec">Table S8</xref>
). Only significant values are reported.</p>
<p>(D) miRNAs presenting a positive-selection signature, as attested by a significant Fay and Wu's <italic>H</italic>
value. The orange and blue stars indicate values that are significant after correction for demography in East Asians and Europeans, respectively.</p>
</caption>
<graphic xlink:href="gr4"></graphic>
</fig>
<table-wrap position="float" id="tbl1"><label>Table 1</label>
<caption><p>SNPs Identified in miRNA Hairpins</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th colspan="2">miRNA<hr></hr>
</th>
<th rowspan="2">Location</th>
<th rowspan="2">Nt.<xref rid="tblfn2" ref-type="table-fn">b</xref>
</th>
<th rowspan="2">dbSNP #</th>
<th rowspan="2">Alleles<xref rid="tblfn3" ref-type="table-fn">c</xref>
</th>
<th colspan="3">Frequency (%)<xref rid="tblfn1" ref-type="table-fn">a</xref>
<hr></hr>
</th>
</tr>
<tr><th>HUGO</th>
<th>Aliases</th>
<th>Africa</th>
<th>Europe</th>
<th>Asia</th>
</tr>
</thead>
<tbody><tr><td><italic>MIR105-2</italic>
</td>
<td>miR-105-2</td>
<td>mirR</td>
<td align="char">15</td>
<td>ss107938236</td>
<td>T/A</td>
<td>-</td>
<td align="char">3.57</td>
<td>-</td>
</tr>
<tr><td><italic>MIR220A</italic>
</td>
<td>miR-220a</td>
<td>mirR</td>
<td align="char">20</td>
<td>ss107938237</td>
<td>T/C</td>
<td align="char">17.91</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR379</italic>
</td>
<td>miR-379</td>
<td>mirR</td>
<td align="char">17</td>
<td>ss107938238</td>
<td>G/A</td>
<td align="char">1.04</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR146A</italic>
</td>
<td>miR-146a</td>
<td>mirR<sup>∗</sup>
</td>
<td align="char">40</td>
<td>rs2910164</td>
<td>G/C</td>
<td align="char">36.46</td>
<td align="char">23.91</td>
<td align="char">55</td>
</tr>
<tr><td><italic>MIR196A2</italic>
</td>
<td>miR-196a-2</td>
<td>mirR<sup>∗</sup>
</td>
<td align="char">54</td>
<td>rs11614913</td>
<td>C/T</td>
<td align="char">16.67</td>
<td align="char">39.13</td>
<td align="char">47.5</td>
</tr>
<tr><td><italic>MIR220A</italic>
</td>
<td>miR-220a</td>
<td>mirR<sup>∗</sup>
</td>
<td align="char">56</td>
<td>ss107938239</td>
<td>C/T</td>
<td>-</td>
<td align="char">3.57</td>
<td>-</td>
</tr>
<tr><td><italic>MIR339</italic>
</td>
<td>miR-339</td>
<td>mirR<sup>∗</sup>
</td>
<td align="char">50</td>
<td>ss107938240</td>
<td>A/G</td>
<td>-</td>
<td align="char">2.17</td>
<td>-</td>
</tr>
<tr><td><italic>MIR92-1</italic>
</td>
<td>miR-92-1</td>
<td>mirR<sup>∗</sup>
</td>
<td align="char">−27</td>
<td>ss107938241</td>
<td>C/T</td>
<td align="char">1.04</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR92-1</italic>
</td>
<td>miR-92-1</td>
<td>mirR<sup>∗</sup>
</td>
<td align="char">−26</td>
<td>rs9589207</td>
<td>G/A</td>
<td align="char">8.33</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR130B</italic>
</td>
<td>miR-130b</td>
<td>Loop</td>
<td align="char">−9</td>
<td>ss107938242</td>
<td>G/A</td>
<td align="char">1.04</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR34A</italic>
</td>
<td>miR-34a</td>
<td>Loop</td>
<td align="char">34</td>
<td>ss107938243</td>
<td>G/A</td>
<td align="char">1.04</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR93</italic>
</td>
<td>miR-93</td>
<td>Loop</td>
<td align="char">32</td>
<td>ss107938244</td>
<td>C/T</td>
<td align="char">1.04</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR96</italic>
</td>
<td>miR-96</td>
<td>Loop</td>
<td align="char">28</td>
<td>rs41274239</td>
<td>T/C</td>
<td>-</td>
<td align="char">2.17</td>
<td>-</td>
</tr>
<tr><td><italic>MIR222</italic>
</td>
<td>miR-222</td>
<td>Loop</td>
<td align="char">−9</td>
<td>ss107938245</td>
<td>G/A</td>
<td align="char">2.99</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR16-1</italic>
</td>
<td>miR-16-1</td>
<td>Stem</td>
<td align="char">42</td>
<td>ss107938246</td>
<td>T/C</td>
<td align="char">4.17</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR106B</italic>
</td>
<td>miR-106b</td>
<td>Stem</td>
<td align="char">35</td>
<td>ss107938247</td>
<td>G/T</td>
<td align="char">2.08</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR10A</italic>
</td>
<td>miR-10a</td>
<td>Stem</td>
<td align="char">−1</td>
<td>ss107938248</td>
<td>A/G</td>
<td align="char">1.04</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR124A2</italic>
</td>
<td>miR-124a-2</td>
<td>Stem</td>
<td align="char">43</td>
<td>ss107938249</td>
<td>A/G</td>
<td>-</td>
<td>-</td>
<td align="char">2.5</td>
</tr>
<tr><td><italic>MIR325</italic>
</td>
<td>miR-325</td>
<td>Stem</td>
<td align="char">−4</td>
<td>ss107938250</td>
<td>G/T</td>
<td align="char">1.49</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR339</italic>
</td>
<td>miR-339</td>
<td>Stem</td>
<td align="char">−8</td>
<td>ss107938251</td>
<td>G/A</td>
<td>-</td>
<td>-</td>
<td>5</td>
</tr>
<tr><td><italic>MIR345</italic>
</td>
<td>miR-345</td>
<td>Stem</td>
<td align="char">−9</td>
<td>ss107938252</td>
<td>C/T</td>
<td>-</td>
<td align="char">2.17</td>
<td>-</td>
</tr>
<tr><td><italic>MIR183</italic>
</td>
<td>miR-183</td>
<td>Stem</td>
<td align="char">25</td>
<td>ss107938253</td>
<td>G/T</td>
<td align="char">3.13</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR215</italic>
</td>
<td>miR-215</td>
<td>Stem</td>
<td align="char">−14</td>
<td>ss107938254</td>
<td>T/C</td>
<td>-</td>
<td align="char">2.17</td>
<td>-</td>
</tr>
<tr><td><italic>MIR199B</italic>
</td>
<td>miR-199b</td>
<td>Stem</td>
<td align="char">−63</td>
<td>ss107938255</td>
<td>C/T</td>
<td align="char">1.04</td>
<td>-</td>
<td>-</td>
</tr>
<tr><td><italic>MIR216A</italic>
</td>
<td>miR-216a</td>
<td>Stem</td>
<td align="char">87</td>
<td>rs41291179</td>
<td>T/A</td>
<td align="char">21.88</td>
<td align="char">4.35</td>
<td>-</td>
</tr>
<tr><td><italic>MIR492</italic>
</td>
<td>miR-492</td>
<td>Stem</td>
<td align="char">84</td>
<td>rs2289030</td>
<td>G/C</td>
<td>-</td>
<td align="char">13.04</td>
<td align="char">25</td>
</tr>
<tr><td><italic>MIR194-2</italic>
</td>
<td>miR-194-2</td>
<td>Stem</td>
<td align="char">62</td>
<td>rs11231898</td>
<td>C/T</td>
<td align="char">5.21</td>
<td>-</td>
<td>-</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="tblfn1"><label>a</label>
<p>The frequencies are relative to the derived state.</p>
</fn>
</table-wrap-foot>
<table-wrap-foot><fn id="tblfn2"><label>b</label>
<p>Nucleotide position relative to the first site of the respective mature miRNA (miR).</p>
</fn>
</table-wrap-foot>
<table-wrap-foot><fn id="tblfn3"><label>c</label>
<p>The first variant corresponds to the ancestral allele as compared to the chimpanzee sequence.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="tbl2"><label>Table 2</label>
<caption><p>miRNA Regions Presenting Robust Signatures of Natural Selection</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th colspan="2">miRNA Region<xref rid="tblfn4" ref-type="table-fn">a</xref>
<hr></hr>
</th>
<th colspan="3">Tajima's <italic>D</italic>
<xref rid="tblfn5" ref-type="table-fn">b</xref>
<hr></hr>
</th>
<th colspan="3">Fu and Li's <italic>F<sup>∗</sup>
</italic>
<xref rid="tblfn5" ref-type="table-fn">b</xref>
<hr></hr>
</th>
<th colspan="3">Fay and Wu's <italic>H</italic>
<xref rid="tblfn5" ref-type="table-fn">b</xref>
<hr></hr>
</th>
<th colspan="3">Population Differentiation (<italic>F</italic>
<sub>ST</sub>
) <xref rid="tblfn5" ref-type="table-fn">b</xref>
<hr></hr>
</th>
</tr>
<tr><th>HUGO</th>
<th>Aliases</th>
<th>AF<xref rid="tblfn6" ref-type="table-fn">c</xref>
</th>
<th>EU<xref rid="tblfn6" ref-type="table-fn">c</xref>
</th>
<th>EAS<xref rid="tblfn6" ref-type="table-fn">c</xref>
</th>
<th>AF</th>
<th>EU</th>
<th>EAS</th>
<th>AF</th>
<th>EU</th>
<th>EAS</th>
<th>EU/AF</th>
<th>EAS/AF</th>
<th>EU/EAS</th>
</tr>
</thead>
<tbody><tr><td><bold><italic>MIR216A</italic>
</bold>
</td>
<td><bold>miR-216a</bold>
</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>−4.502<sup>∗∗</sup>
</td>
<td></td>
<td>0.352<sup>∗</sup>
</td>
<td></td>
</tr>
<tr><td><italic>MIR198</italic>
</td>
<td>miR-198</td>
<td></td>
<td></td>
<td>−1.716<sup>∗</sup>
</td>
<td></td>
<td></td>
<td>−2.948<sup>∗∗</sup>
</td>
<td></td>
<td></td>
<td>−5.001<sup>∗∗</sup>
</td>
<td></td>
<td></td>
<td>0.416<sup>∗</sup>
</td>
</tr>
<tr><td><italic>MIR148A</italic>
</td>
<td>miR-148a</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>−4.862<sup>∗∗</sup>
</td>
<td>0.373<sup>∗</sup>
</td>
<td>0.497<sup>∗</sup>
</td>
<td>0.278<sup>∗</sup>
</td>
</tr>
<tr><td><bold><italic>MIR106B, MIR93</italic>
</bold>
, <italic>MIR25</italic>
</td>
<td><bold>miR-106b, miR-93</bold>
, miR-25</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>−3.214<sup>∗∗</sup>
</td>
<td></td>
<td></td>
<td>−2.993<sup>∗</sup>
</td>
<td>−3.191<sup>∗</sup>
</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr><td><bold><italic>MIR183, MIR96</italic>
</bold>
</td>
<td><bold>miR-183, miR-96</bold>
</td>
<td></td>
<td></td>
<td>−1.759<sup>∗</sup>
</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>0.284<sup>∗</sup>
</td>
</tr>
<tr><td><italic>MIR370</italic>
<xref rid="tblfn7" ref-type="table-fn">d</xref>
</td>
<td>miR-370</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>−5.530<sup>∗∗</sup>
</td>
<td></td>
<td>0.402<sup>∗</sup>
</td>
<td>0.329<sup>∗</sup>
</td>
</tr>
<tr><td><italic>MIR494</italic>
<xref rid="tblfn7" ref-type="table-fn">d</xref>
</td>
<td>miR-494</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>−3.814<sup>∗</sup>
</td>
<td></td>
<td></td>
<td></td>
<td>0.402<sup>∗</sup>
</td>
</tr>
<tr><td><italic>MIR382,</italic>
<xref rid="tblfn7" ref-type="table-fn">d</xref>
<italic>MIR134</italic>
<xref rid="tblfn7" ref-type="table-fn">d</xref>
</td>
<td>miR-382, miR-134</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>−4.577<sup>∗</sup>
</td>
<td></td>
<td></td>
<td></td>
<td>0.442<sup>∗∗</sup>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn><p>miRNAs in bold correspond to those in which SNPs have been identified in their hairpin structure (<xref rid="tbl1" ref-type="table">Table 1</xref>
). The miRNA regions included in this table correspond to those that, after correction for both demographic models, kept rejecting neutrality for at least two independent tests of selection. These conservative criteria are intended to minimize the rate of false positive signatures of selection. The full list of miRNA regions rejecting neutrality for at least one neutrality test can be found in <xref rid="app2" ref-type="sec">Table S5</xref>
.</p>
</fn>
</table-wrap-foot>
<table-wrap-foot><fn id="tblfn4"><label>a</label>
<p>miRNAs in the same line are organized in clusters.</p>
</fn>
</table-wrap-foot>
<table-wrap-foot><fn id="tblfn5"><label>b</label>
<p>Significant results after correction for demography: <sup>∗</sup>
p < 0.05, <sup>∗∗</sup>
p < 0.01.</p>
</fn>
</table-wrap-foot>
<table-wrap-foot><fn id="tblfn6"><label>c</label>
<p>AF = Yoruba and Chagga from sub-Saharan Africa, EU = Danes from Europe, and EAS = Han Chinese from East Asia.</p>
</fn>
</table-wrap-foot>
<table-wrap-foot><fn id="tblfn7"><label>d</label>
<p>The miRNAs contained in these regions are located in the so-called small-RNA-rich island on chromosome 14.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</floats-wrap>
</pmc>
</record>
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