<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Imprialou M</submitter><funding>Wellcome Trust</funding><funding>Biotechnology and Biological Sciences Research Council</funding><funding>NIGMS NIH HHS</funding><pagination>1425-1441</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC5378104</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>205(4)</volume><pubmed_abstract>To understand the population genetics of structural variants and their effects on phenotypes, we developed an approach to mapping structural variants that segregate in a population sequenced at low coverage. We avoid calling structural variants directly. Instead, the evidence for a potential structural variant at a locus is indicated by variation in the counts of short-reads that map anomalously to that locus. These structural variant traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between a structural variant trait at one locus, and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3×) population sequence data from 488 recombinant inbred &lt;i>Arabidopsis thaliana&lt;/</pubmed_abstract><journal>Genetics</journal><pubmed_title>Genomic Rearrangements in &amp;lt;i&amp;gt;Arabidopsis&amp;lt;/i&amp;gt; Considered as Quantitative Traits.</pubmed_title><pmcid>PMC5378104</pmcid><funding_grant_id>BBS/E/J/000PR9795</funding_grant_id><funding_grant_id>BBS/E/J/000PR9797</funding_grant_id><funding_grant_id>BB/M003809/1</funding_grant_id><funding_grant_id>T32 GM007464</funding_grant_id><funding_grant_id>BB/F022697/1</funding_grant_id><funding_grant_id>090532/Z/09/Z</funding_grant_id><pubmed_authors>Bhomra A</pubmed_authors><pubmed_authors>Stegle O</pubmed_authors><pubmed_authors>Mott R</pubmed_authors><pubmed_authors>Steffen JG</pubmed_authors><pubmed_authors>Greenhalgh R</pubmed_authors><pubmed_authors>Robert-Seilaniantz A</pubmed_authors><pubmed_authors>Kover P</pubmed_authors><pubmed_authors>Kahles A</pubmed_authors><pubmed_authors>Clark RM</pubmed_authors><pubmed_authors>Ratsch G</pubmed_authors><pubmed_authors>Imprialou M</pubmed_authors><pubmed_authors>Visscher A</pubmed_authors><pubmed_authors>Tsiantis M</pubmed_authors><pubmed_authors>Nordborg M</pubmed_authors><pubmed_authors>Belfield E</pubmed_authors><pubmed_authors>Goram R</pubmed_authors><pubmed_authors>Hein J</pubmed_authors><pubmed_authors>Lempe J</pubmed_authors><pubmed_authors>Jones J</pubmed_authors><pubmed_authors>Harberd NP</pubmed_authors><pubmed_authors>Gan X</pubmed_authors><pubmed_authors>Osborne EJ</pubmed_authors></additional><is_claimable>false</is_claimable><name>Genomic Rearrangements in &amp;lt;i&amp;gt;Arabidopsis&amp;lt;/i&amp;gt; Considered as Quantitative Traits.</name><description>To understand the population genetics of structural variants and their effects on phenotypes, we developed an approach to mapping structural variants that segregate in a population sequenced at low coverage. We avoid calling structural variants directly. Instead, the evidence for a potential structural variant at a locus is indicated by variation in the counts of short-reads that map anomalously to that locus. These structural variant traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between a structural variant trait at one locus, and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3×) population sequence data from 488 recombinant inbred &lt;i>Arabidopsis thaliana&lt;/</description><dates><release>2017-01-01T00:00:00Z</release><publication>2017 Apr</publication><modification>2026-05-30T12:06:39.759Z</modification><creation>2019-03-27T02:40:11Z</creation></dates><accession>S-EPMC5378104</accession><cross_references><pubmed>28179367</pubmed><doi>10.1534/genetics.116.192823</doi></cross_references></HashMap>