{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T02:51:46Z","timestamp":1791427906690,"version":"4.3.3"},"reference-count":62,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ecology and Evolution"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Environmental stressors such as ultraviolet radiation impose strong selective pressures on organisms, yet how adaptation to such stressors shapes transcriptomic responses at the network level remains poorly understood. Although stratospheric ozone is recovering globally, substantial regional variation in UV exposure persists, particularly in high\u2010altitude environments where extreme UV levels can occur. Here, we compared three fish models representing distinct biological responses to UVB exposure: wild\u2010type zebrafish (\n                    <jats:styled-content style=\"fixed-case\">\n                      <jats:italic>Danio rerio<\/jats:italic>\n                    <\/jats:styled-content>\n                    ), a melanin\u2010deficient zebrafish mutant (\n                    <jats:italic>nacre<\/jats:italic>\n                    ) lacking a major protective mechanism against UVB damage, and the high\u2010altitude Andean killifish\n                    <jats:styled-content style=\"fixed-case\">\n                      <jats:italic>Orestias ascotanensis<\/jats:italic>\n                    <\/jats:styled-content>\n                    , a species naturally exposed to extreme UVB radiation. Together, these models define a gradient spanning physiological protection, impaired protection, and evolutionary adaptation to UVB stress. Using RNA\u2010seq and protein\u2013protein interaction networks, we show that transcriptomic responses differ markedly across this gradient. Wild\u2010type and\n                    <jats:italic>nacre<\/jats:italic>\n                    zebrafish exhibited relatively limited transcriptomic changes (\u223c2%\u20132.4% of genes changing), whereas\n                    <jats:styled-content style=\"fixed-case\">\n                      <jats:italic>O. ascotanensis<\/jats:italic>\n                    <\/jats:styled-content>\n                    displayed a large\u2010scale and highly coordinated response (\u223c21.6% of genes changing) characterized by functionally specialized networks enriched in DNA repair pathways. These differences involved not only transcriptomic magnitude but also marked reorganization of transcriptomic architecture. Integration with positive selection analyses revealed that positively selected genes were concentrated within highly interconnected regions of transcriptomic networks, consistent with adaptation involving network reorganization. Furthermore, ortholog\u2010based analyses suggest that adaptive responses involve differential reorganization of a conserved functional background. Together, our results support a model in which adaptation to environmental stress is associated with the reorganization of conserved transcriptomic networks across physiological and evolutionary contexts, providing a systems\u2010level perspective on the molecular basis of adaptation.\n                  <\/jats:p>","DOI":"10.1002\/ece3.74298","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T09:51:26Z","timestamp":1788429086000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evolutionary Reorganization of Transcriptomic Architecture Across a\n                    <scp>UVB<\/scp>\n                    Tolerance Gradient in Fish"],"prefix":"10.1002","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3479-2583","authenticated-orcid":false,"given":"Camilo","family":"Valdivieso","sequence":"first","affiliation":[{"name":"Center for Genome Regulation  Santiago Chile"},{"name":"Laboratorio de Gen\u00f3mica y Gen\u00e9tica Molecular, Departamento de Biolog\u00eda, Facultad de Ciencias Universidad de Chile  Santiago Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miguel Luis","family":"Allende","sequence":"additional","affiliation":[{"name":"Center for Genome Regulation  Santiago Chile"},{"name":"Laboratorio de Gen\u00f3mica y Gen\u00e9tica Molecular, Departamento de Biolog\u00eda, Facultad de Ciencias Universidad de Chile  Santiago Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1039\/c7pp00236j"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1089072"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.3389\/fmars.2022.966654"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg1272"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s43630\u2010023\u201000371\u2010y"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0502311102"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12862\u2010017\u20100958\u20103"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1089118"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1111\/php.12368"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1128\/microbiolspec.funk\u20100037\u20102016"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty560"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1186\/1752\u20100509\u20108\u2010S4\u2010S11"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10482\u2010018\u20101075\u2010z"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41559\u2010023\u201002249\u20109"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0190152"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/gigascience\/giab008"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1159\/000064535"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ygeno.2021.12.018"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts635"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jproteome.2c00651"},{"key":"e_1_2_10_22_1","doi-asserted-by":"crossref","unstructured":"Edwards J. 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